Data Analytics Engineer Resume Samples

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Guide the recruiter to the conclusion that you are the best candidate for the data analytics engineer job. It’s actually very simple. Tailor your resume by picking relevant responsibilities from the examples below and then add your accomplishments. This way, you can position yourself in the best way to get hired.

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  • Tailor your resume by selecting wording that best fits for each job you apply

MB
M Bergstrom
Matilde
Bergstrom
3689 Bechtelar Pines
New York
NY
+1 (555) 763 7582
3689 Bechtelar Pines
New York
NY
Phone
p +1 (555) 763 7582
Experience Experience
04/2016 present
Detroit, MI
Senior Principal Big Data Analytics Engineer
Detroit, MI
Senior Principal Big Data Analytics Engineer
04/2016 present
Detroit, MI
Senior Principal Big Data Analytics Engineer
04/2016 present
  • Reproduce customer issues and resolve them by either establishing a workaround or a solution, or by debugging and creating a bug fix
  • Develops and/or executes implementation according to project plans and priorities
  • Responsible for the design, development, testing, documentation and analysis of modules or features of new or upgraded software systems and products
  • Responsible for handling critical customer problems in real-time and developing code fixes or enhancements to be included in future code releases or patches
  • May participate in development in any of a range of product areas such as thin client, rich client, server, installation, communication layers, and so forth
  • Provide technical leadership to the team
  • Provides estimated timelines for issues reported from the field
04/2013 02/2016
Boston, MA
Senior Data Analytics Engineer
Boston, MA
Senior Data Analytics Engineer
04/2013 02/2016
Boston, MA
Senior Data Analytics Engineer
04/2013 02/2016
  • Drive increased efficiency across the teams, eliminating duplication, leveraging product and technology reuse
  • Work on core data structures and algorithms and implement them using technology chosen
  • Conduct data quality profiling analysis, recommend data quality rules and processes
  • Lead analytics framework development, working closely with analytics researchers, data scientists, mechanical, electrical, petroleum and chemical engineers
  • Liaise Technically with other departments, including Global research centres and other GE Digital analytics groups
  • Understand performance parameters and assess data processing performance
  • Design and develop GIS data processing and visualization algorithms
01/2007 10/2012
Phoenix, AZ
Data Analytics Engineer
Phoenix, AZ
Data Analytics Engineer
01/2007 10/2012
Phoenix, AZ
Data Analytics Engineer
01/2007 10/2012
  • Perform data-extraction, transformation and loading (ETL) development and programming
  • Develop and perform experimental design approaches to validate findings or test hypotheses
  • Work with the software engineering group to design and develop data models conducive to analytic environment
  • Develop dashboards and reports that maximize use of stakeholder time and effort by providing high-value information quickly and easily
  • Working with the engineering team to make sure that we have the right data ingestion in place
  • Familiar with the workings of network, servers, AWS infrastructure & cloud services
  • Design and implement reporting solutions enabling stakeholders to manage the business and make effective decisions
Education Education
Bachelor’s Degree in Computer Science
Bachelor’s Degree in Computer Science
University of Virginia
Bachelor’s Degree in Computer Science
Skills Skills
  • Strong writing and client facing communications with the ability to effectively develop and maintain client relationships
  • Advanced knowledge of professional standards and technology trends within the analytics industry
  • Experience with ensuring data consistency, discoverability, and quality
  • Be proactive and passionate about delivering good quality product with efficient time management practices
  • Good understanding of Data mining & Machine learning techniques
  • Action oriented and able to prioritize while handling multiple tasks
  • 4+ years of successfully designing and implementing data-centric applications, such as data warehouses, operational data stores, analytical engines and data integration projects
  • Powerful hands-on SQL based data extraction skills to manipulate data from common relational database systems (Oracle, SQL Server), distributed systems (Amazon Redshift, Teradata), NoSQL databases (Mongo DB) and cloud based services (like Salesforce, Workday, etc.)
  • Proficient in at least one of the commonly used ETL or data integration tool like Microsoft’s SSIS, Informatica, SnapLogic, PL/SQL, or any other open source tool
  • Database and SQL performance tuning capabilities including partitioning, indexing, compression and other techniques for DB structures like tables, views, procedures and user defined functions
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1

Big Data Analytics Engineer Resume Examples & Samples

  • Contribute to the team spirit of an international team and serve customers all over the world
  • 4 years of experience developing solutions in .Net
  • Strong database skills (MS SQL, T-SQL)
  • Experience solving complex and large-scale software problems
  • Clear understanding of Web services approach including web service protocols such as SOAP,REST and oData
  • Experience working with latest NoSql database technologies
2

Data Analytics Engineer Resume Examples & Samples

  • Design, develop and deploy solutions around business needs
  • 3 years of experience developing solutions in .Net
  • Extensive experience with the .NET 4.0/4.5 framework, including C#, Entity Framework, WCF, oData, XML
  • Strong database skills (MS SQL, T-SQL) experience working with MapReduce, Pig and Hive is helpful
  • Fluent written and spoken English is essential
  • Experience in additional programming languages including Python and Java
  • Experience working with cloud computing environments
  • Knowledge of design patterns. Experience with UML
  • Experience with SOA implementation
  • Ability to tune solutions to improve performance and end-user experience
3

Big Data Analytics Engineer Resume Examples & Samples

  • Contribute to all applied engineering activities (requirements gathering, project planning, etc.)
  • Participate in design session with application team
  • Develop code for any customization required
  • Hadoop SME and provide Level 3 technical support for troubleshooting
  • 3+ years overall IT experience
  • High proficiency in software development, specifically in Java
  • Previous experience Big Data experience using HDFS, MapReduce, Hive, HBase, Pig, Sqoop, and Flume
  • Experience with Red Hat Linux, UNIX Shell Scripting, SQL and RDBMS
  • Good interpersonal with excellent communication skills - written and spoken English
  • Able to interact with client projects in cross-functional teams
  • Ability to create documents of high quality
  • Ability to work in a structured environment and follow procedures, processes and policies
  • Self-starter who works with minimal supervision
  • Ability to work in a team of diverse geographies and skill sets
4

Big Data Analytics Engineer Resume Examples & Samples

  • Architect and engineer a Citi Online Data Archival Platform on Hadoop for all types of structured and unstructured data
  • Integrate Citi supported Big Data solutions with the Archival Platform for data ingestion, data management, and data access and analytics
  • Engineer and integrate data management with Vendor and Citi metadata and data management solutions
  • Architect and engineer Citi Log Management Platform on Hadoop to centrally store machine generated log data from multiple sources and enable near real-time analytics for quick time to insight
  • Actively engage with businesses, Chief Data Office and operation team to provide engineering support and architecture design for application POC and use case deployments
  • Develop user interfaces or templates to ease application on-boarding and customization
  • Work with cross domain teams to develop Citi standard platforms
  • Provide SME and Level 3 technical support for troubleshooting
  • Experience with HDFS, MapReduce, Sqoop, Hive, HBase, Flume, Impala, Solr and Talend
  • Experience with Cloudera distribution (CDH) and Cloudera Manager is preferred
  • Good application development experience with Red Hat Linux, UNIX Shell Scripting, Java, RDBMS, NoSQL, and ETL solutions
  • Exposure to Citigroup internal standards, policies and procedures is a plus (does not apply to external candidates)
5

Big Data Analytics Engineer Resume Examples & Samples

  • Contribute to all Applied Engineering activities (requirements gathering, project planning, etc.)
  • Hadoop SME and provide Level-3 technical support for troubleshooting
  • Ability to work in a team of diverse skill sets and geographies
6

Big Data Analytics Engineer Resume Examples & Samples

  • Knowledge of the data management eco-system including concepts of data warehousing, snowflake schemas and ETL. You should not only be proficient in SQL, but be so with different RDBMs
  • Solid working experience with Java programming language and open source frameworks. You should know your way around Maven, Git, etc
  • Proficient experience with Python and/or shell scripting
  • Experience in Unix system programming and administration: user/group/rights, process management, log management, networking
  • Good knowledge of TCP and HTTP or proven experience with multi-tier enterprise applications
  • Experience with messaging systems (MQs) desired
  • Ideally you have had experience, at professional or personal level, with Apache and Hadoop eco-system. You should be familiar with Map Reduce and be able to model different data problems in MR terms
  • Good aptitude in multi-threading, concurrently, performance, memory-efficiency
  • Good written and spoken English
  • Committed to excelling in their job and enjoys delivering accurate and efficient work products
  • A team-first attitude and the flexibility to change tasks as the project requirements change
  • Motivation to support others, to share information and knowledge and to work effectively towards shared goals
  • Can explain complex ideas clearly
  • Proactive in seeking help when needed, happy to admit when don't understand something
  • A desire to excel in one’s job, by actively learning about new technologies and gaining insight into the business we serve
7

Lead Big Data Analytics Engineer Resume Examples & Samples

  • Provide technology leadership in development of Business Intelligence services by helping to drive project planning, estimation, budget, resource forecasting, and technology planning
  • Partner with application developers, architects, engineers, and various groups supporting loyalty applications to drive new initiatives
  • Work closely with data architects, application development, ETL development team to design and implement BI applications using shared architecture and Enterprise Data Warehouse
  • Mentor team members, develop departmental procedures and best practices standards
  • Lead development and oversee programming and testing functions to ensure that projects are securely delivered and fulfill expectations
  • Conduct training for internal reporting team and end-user training for both technical and business users
  • Undergraduate degree in Computer Science, Electrical Engineering, Information Systems or other technical discipline required; advanced degree preferred
  • Minimum of 10 years of software development management experience (with a concentration in data centric initiatives), with demonstrated expertise in leveraging standard development best practice methodologies
  • Minimum of 4 or more years of hands-on Object Oriented Programming Experience in .Net, C, C# Or Java technology stack, Hadoop and Big Data tools & applications, on Microstrategy, Tableau and other BI Platforms
  • Relational database and SQL development experience required; extensive knowledge of UDB (3 years of experience or more) and other relational databases (such as Oracle) a plus
  • Strong communication skills with proven ability to present complex ideas and document in a clear and concise way
  • Knowledge of Visa applications a plus
  • Quick learner; self-starter, detailed and thorough
8

Lead Data Analytics Engineer Resume Examples & Samples

  • 5+ years in data warehousing and database design
  • Demonstrated knowledge of data warehousing/business intelligence best practices, methodologies, standards, and architectures
  • Extensive knowledge of relational database design, logical data modeling, data warehousing, and relational database management systems
  • Knowledge of web analytics platforms like Google Analytics, Webtrends, and/or Omniture/Adobe Analytics
  • Experience with Ruby, Node.js and Redshift
9

Data & Analytics Engineer Resume Examples & Samples

  • Analyze data from internal and external sources
  • Augment, document, and understand current ETL process
  • Familiarity with creating reports using our current (and future) BI tools – SAP Hana, Lumira, Google Analytics Premium, Tableau, Redshift, PostgreSQL, MySQL, Excel, etc
  • Strong business perspective; able to merge business questions/needs with available data to provide data-driven insights
  • Field quick-turn requests for ad hoc analytics
  • Have entrepreneurial nature to help to implement better process
  • Create new ETL scripts for new data sources and reports
  • Think about data and data modeling in context of a platform that spans both mobile and web and a business that spans advertising, subscription services, retail, wholesale and e-commerce
  • 5+ Years experience working in a data engineering/programming capacity
  • Very strong written, verbal, and interpersonal skills
  • Strong proficiency with SQL – queries AND writing stored procedures (SAP HANA, MySQL, PostgreSQL, etc.)
  • Strong Python programming skills
  • Ability to articulate the benefits of different approaches to data warehousing and the implications to business intelligence
  • Strong knowledge of statistical concepts, terms, and calculations
  • Google analytics – including events, conversions (GAP a plus!)
  • Mobile analytics and retail/ecommerce analytics
  • Willingness to take initiative to contribute beyond basic responsibilities — be a leader not a follower
  • Ability to thrive in a startup environment – comfortable with ambiguity and operating in a collaborative environment
  • JavaScript and experience with JS visual libraries
  • Experience with sensor/performance and geospatial data
  • Experience with Hadoop, Spark or other big data technologies
10

Data Analytics Engineer Internship Resume Examples & Samples

  • Develop program by following analytical solutions to help solve business problems
  • Develop analytical solutions through the design, programming and implementation of business intelligence and data-warehouse constructs and presentation layers
  • Design and develop data-sets to support analyses
  • Perform data-extraction, transformation and loading (ETL) development and programming
  • Design and build information-delivery systems and solutions
  • Must be a self-motivated, energetic, detail oriented team player passionate about producing high quality BI & analytics deliverables and thrives in a collaborative environment
  • Solid engineering background with SQL, familiar with Linux script, Java or Python
  • Familiar with data mining and machine learning
  • Knowledge of Hadoop, Hive, and Pig preferred
11

Data Analytics Engineer Resume Examples & Samples

  • Monitor and validate the daily data flow and quality
  • Perform data-mining, data analysis and performance measurements on business-information systems utilizing analytics tools and methodologies
  • Develop data pipeline to support application engineers to use data to implement personalization and recommendation
  • Implement process improvements and enhancements
  • Solid engineering background with SQL, Linux script, Java or Python
  • Solid background with data mining and machine learning
  • Good background with statistics skills such as R
12

Big Data & Analytics Engineer Resume Examples & Samples

  • Provide SME and Level-3 technical support
  • Understanding of analytics concepts, model development and BI
  • Knowledge of the Hadoop ecosystem – HDFS, MapReduce, Hive, etc
  • Experience developing Hadoop integrations for data ingestion, data mapping and data processing capabilities
  • Experience with large scale ETL, BI or Analytical platforms
  • Experience with installation, validation, testing, and packaging on Red Hat Linux and Wintel platforms
  • Any experience in Hadoop (Cloudera preferred), ETL (Talend, AbInitio), MapReduce, Hive, Pig, HBase, Java, C++, Perl, or Python
  • Any experience in analytical techniques such as time series analysis, regression analysis, or other
  • Any experience with statistical analysis software, such as Weka, R, Rapid-Miner, Matlab, SAS, and SPSS
  • Any past experience with optimizing computing techniques i.e., parallel processing, grid computing, etc
  • Good interpersonal with excellent communication skills
  • Good team player interested in sharing knowledge and cross-training other team members
13

Data Analytics Engineer Resume Examples & Samples

  • 3+ years of Software Engineering experience
  • BS Engineering/Computer Science or equivalent experience required
  • Exercises independent judgment with direction from supervisor
  • Interface with other technical personnel or team members to finalize requirements
  • Write and review portions of detailed specifications for the development of system components of moderate complexity
  • Work closely with other development team members to understand moderately complex product requirements and translate them into software designs
  • Successfully implement development processes, coding best practices, and code reviews
  • Resolve technical issues as necessary
  • Complete bug fixes
  • Verbal and written communication skills, problem solving skills, customer service and interpersonal skills (Required)
  • Ability to work independently and manage one’s time (Required)
  • Knowledge of the full software development lifecycle: from business/systems analysis, through requirements gathering and functional specification authoring, to development, testing and delivery (Required)
  • Ability to troubleshoot issues and make system changes as needed to resolve issue
  • Knowledge of software, such as ECL, SQL, C/C++, Java, J2EE, etc (Required)
14

Senior Data Analytics Engineer Resume Examples & Samples

  • Architect, design, and develop new data integration algorithms to enable customer performance analytics products
  • Work across cross-functional teams and own the data solutions end-to-end
  • Perform new data acquisition impact analysis
  • Conduct data quality profiling analysis, recommend data quality rules and processes
  • Design and develop data governance processes and procedures
  • Design and develop new data acquisition ingestion processes
  • Design and develop data standardization and validation algorithms
  • Design and develop GIS data processing and visualization algorithms
  • Design and develop data cleansing algorithms
  • Lead and execute data integration and product fulfillment projects
  • Collaborate with business analysts, architects, frontend developers and software developers to implement data solutions that are aligned with and extend shared platforms and solutions
  • Work with data operations teams to iteratively create business processes
  • Drive increased efficiency across the teams, eliminating duplication, leveraging product and technology reuse
  • Support process improvements which guide the development, sustaining & support activities
  • Work cross functionally with other business departments to align activities and deliverables
  • Proactively share information across the team, to the right audience with the appropriate level of detail and timeliness
  • Apply principles of SDLC and methodologies like Lean/Agile/XP, CI, software and product security, scalability, documentation practices, refactoring and automated testing techniques
  • Write data processing code that meets standards and delivers desired functionality using the technology selected for the project
  • Understand performance parameters and assess data processing performance
  • Work on core data structures and algorithms and implement them using technology chosen
  • Drive world-class quality in the development and support of products
  • Bachelor’s Degree in Computer Science or in “STEM” Majors (Science, Technology, Engineering and Math)
  • A minimum of 5 years of professional experience OR Master’s degree with 3 years of experience
15

Data Analytics Engineer Resume Examples & Samples

  • Bachelor's Degree in Computer Science, Information Technology or equivalent (STEM) with minimum 5 years of experience as data engineer / scientist / analyst
  • Minimum of 2 year of experience using analytics tools such as R and/or MATLAB
  • Minimum of 2 years of experience using JSON, Map-Reduce, Spark
  • Minimum of 2 year of experience using Scripting (Pig, Python, Perl, etc)
  • Minimum of 2 years of experience with Core Java, Java Web Services development SOAP, REST APIs
  • Minimum of 3 year of experience working on Database(s), SQL
  • Statistics background
  • Experience with tools such as GITHub
  • Primary role in recent positions must be as a Lead Data / Big Data Engineer
  • Must have superior communication skills - both oral and written
16

Data Analytics Engineer Resume Examples & Samples

  • Gather reporting and analysis requirements and translate into reporting structures data models, including aggregate tables, pivoted tables, and relational and dimensional (star-schema) marts
  • Profile and analyze source data to determine the best reporting structures to build
  • Create source-2-target mappings and other technical system specific documents to support data integration
  • Design and develop ETL code to load and transform this source data in various formats (including key-value pair and variable-structure data) according to business requirements into a SQL/SQL like database
  • Conduct ETL, SQL and DB performance tuning, troubleshooting, support, and capacity estimation to ensure highest data quality standards
  • Aid in the development of unit test plans and test cases
  • Provide day-to-day support and mentoring to end users who are interacting with the data
  • Bachelor's degree in related area (Computer Science, Information Systems, Engineering, Statistics) or an equivalent combination of education and experience
  • 4+ years of successfully designing and implementing data-centric applications, such as data warehouses, operational data stores, analytical engines and data integration projects
  • Powerful hands-on SQL based data extraction skills to manipulate data from common relational database systems (Oracle, SQL Server), distributed systems (Amazon Redshift, Teradata), NoSQL databases (Mongo DB) and cloud based services (like Salesforce, Workday, etc.)
  • Proficient in at least one of the commonly used ETL or data integration tool like Microsoft’s SSIS, Informatica, SnapLogic, PL/SQL, or any other open source tool
  • Database and SQL performance tuning capabilities including partitioning, indexing, compression and other techniques for DB structures like tables, views, procedures and user defined functions
  • Strong understanding and experience in 3NF & dimensional (STAR schema) approaches for data warehouse environment
  • Proficient in creating scripts in at least one of the programming language (either Shell, Unix, python, Java, R or VB)
  • Experience with Business Intelligence and reporting tools (preferably Tableau, R, SSRS)
  • Knowledgeable, passionate and eager to learn about emerging technologies & frameworks such as Hadoop, cloud based distributing computing and other open source approaches
  • Familiar with the workings of network, servers, AWS infrastructure & cloud services
  • Demonstrated experience translating business and technical requirements into data models
  • Ability to work independently on assignments with little oversight
  • High aptitude for logical thinking and problem solving techniques
  • Be proactive and passionate about delivering good quality product with efficient time management practices
  • Ability to sense risks and research issues before hand so as to analyze underlying problems before recommending possible solutions
  • Strong interpersonal skills (including written and verbal communication) to work effectively in a team environment and also part of a matrix organization
  • Work with a culturally diverse team from varying backgrounds
  • Must be flexible for changing business requirements and assignments with an ability to work on multiple projects simultaneously
  • Proven ability to mentor and develop others and help them grow their skills
  • Has a positive and creative attitude to unknown challenges
17

Data Analytics Engineer Resume Examples & Samples

  • MS in Computer Science or Computer Engineering and three (3) years of work experience
  • 3 to 10 years of experience with bid data analytics and supporting platforms (Hadoop, Apache Spark, others)
  • Experience with software development, storage architectures, and network design
  • Experience supporting non-technical customers with technical analysis or tools
  • Outstanding Customer Service Skills
  • Experience supporting review of technical proposals
18

Data Analytics Engineer Resume Examples & Samples

  • Experience in UNIX System Administration and networking including working knowledge of TCP IP, DNS, HTTPS/SSL, load balancing etc
  • Working experience in server configuration management and virtual private cloud setups (esp. for distributed computing; example hipaa-compliant setups for sufficient data protection)
  • Understanding of container technologies (Docker, Kubernetes, Mesos, etc.)
  • Familiarity with Big Data technologies in Hadoop ecosystem
  • Good understanding of SDLC, Agile methodologies and scrum development
19

Data Analytics Engineer Resume Examples & Samples

  • Develop dashboards and reports that maximize use of stakeholder time and effort by providing high-value information quickly and easily
  • Drive the evolution of a data warehouse that supports current and future reporting needs
  • Aggregate data from multiple sources including sales, operations, product, and customer databases to create integrated views that can be used to drive decision making
  • Work with the software engineering group to design and develop data models conducive to analytic environment
  • Analyze new and existing business processes utilizing metrics and analytics tools, and make suggestions for change
  • BA/BS in computer science, math, a related field, or relevant work experience
  • Expert knowledge of SQL and relational databases such as Oracle, Postgres, MySQL (queries, tuning, PL/SQL), including knowledge of techniques for querying large datasets
  • Proficiency with data warehouse design and maintenance, including ETL/ELT
  • Proficiency with Business Intelligence software tools (report creation and maintenance, custom query creation, optimization); experience with Tableau is a plus
  • Proficiency designing a range of visualizations
  • Demonstrable experience with a scripting language such as python
  • Proficiency in eliciting business requirements from stakeholders in a variety of business areas
20

Big Data Analytics Engineer Resume Examples & Samples

  • Master’s Degree in Computer Science, Engineering, or a related field
  • 3+ years post education work experience
  • Strong object oriented and or functional programming experience with at least 3+ years of experience using Python
  • Experience with virtualized infrastructure and Infrastructure as a Service (IaaS) such as Amazon Web Services, or Google Compute Engine
  • Experience with Big data ecosystem including Hbase, MongoDB, MapReduce, and Spark
  • Understanding of developing systems and software around API’s and creating services and micro services
  • Excellent project management skills, demonstrated ability to deliver detailed technical documentation and manage tasks
  • Comfortable working in a dynamic environment and developing flexible solutions to meet evolving requirements
21

Thermal Data Analytics Engineer Resume Examples & Samples

  • The ideal candidate will have 5+ years of industry experience, having been involved in the optimization of consumer electronic devices. Experience in some of the following fields is required
  • Applied Statistics or Informatics
  • Computer Science or Computer Engineering
  • Large-scale data collection and analysis
  • General programming/scripting knowledge including R, Perl, Python, JMP
  • Experience in the following areas is highly desirable
  • Thermal Management
  • Algorithm Development § Operating Systems
  • Control Systems
22

Big Data Analytics Engineer Resume Examples & Samples

  • Understanding of and passion for statistical data analysis
  • Experience in building large scale real-world backend and middle-tier systems in Java
  • Understanding of scaling Big Data applications
  • Knowledge of Hadoop, Hbase, Zookeeper
  • Understanding of R or other statistical computing packages (commons-math)
  • Agile software development experience
  • Highly motivated, self-directed, fast learner
23

Data Analytics Engineer, Senior Resume Examples & Samples

  • Experience with retrieving data from relational database systems with SQL
  • Experience with dynamic data reporting or business intelligence solutions, including SAS, TIBCO Spotfire, or Tableau
  • Knowledge of R and Scala
  • Knowledge of statistics, algebra, and calculus
  • BA or BS degree and 6 years of experience with developing data analytics solutions or MA or MS degree and 4 years of experience with developing data analytics solutions
  • Experience in developing solutions with Amazon Web Services
  • Experience with NoSQL databases, including MongoDB and Accumulo
  • Knowledge of modern enterprise platform architectures and technology stack, including big data storage and processing solutions
  • Security+ or CISSP Certification
24

Lead Advanced Data Analytics Engineer Resume Examples & Samples

  • Bachelor's degree
  • 2 years previous experience with advanced SQL expertise and data modeling
  • 2 years advanced Unix / Linux skills
  • 2 years minimum experience with ETL and data movement tools experience including: Data Stage, Sqoop, and Pivotal Data Loader
  • 2 years previous experience with relational databases: MySQL, Postgres, DB2 or Greenplum
  • Programming experience, ideally in Python or Java
  • Experience processing large amounts of structured and unstructured data
  • Map Reduce experience is a plus
  • Able to work in teams and collaborate with others to clarify requirement
  • Ability to tune Hadoop solutions to improve performance and end-user experience
25

Data Analytics Engineer Resume Examples & Samples

  • Work with business customers in understanding the business requirements and implementing solutions to support analytical and reporting needs of Fulfillment Centers
  • Develop and integrate analytics solutions to transform sensor data to actionable information
  • Conduct ad-hoc data analysis and data quality investigations
  • BS, MA or PhD in Statistics, Mathematics, Computer Science, Machine Learning, or related field
  • At least 5 years work experience in a related field
  • At least 3 years of relevant experience with ETL, data mining, SQL, reporting, and statistical modeling
  • Great skills using SQL, BI Reporting tools and databases in a business environment
  • Experience with at least one language (shell script, Perl, Ruby, PHP, Scala, etc)
  • Advanced knowledge in data analysis and statistical modeling; data management and quality control
  • Unwavering attention to detail
  • Experience working with business customers to drive requirement analysis
  • Strong record of performance and delivery results; think big, start small, grow fast
  • Experience with SCADA
  • Experience with RFID systems
  • Experience with Stata, R, SAS BI, Cognos, OBIEE, Tableau or other software packages
  • Experience with Spark, Storm, Kafka, or Hadoop
26

Tpce Data Analytics Engineer Resume Examples & Samples

  • Perform technical and operational analysis for global data, manufacturing performance, and yield analysis
  • Drive new analytics, reporting and automation capabilities including the use of advanced statistical algorithms
  • Provide management updates on program milestones, project development roadmaps, wins and challenges in support of backend operation’s differentiated capabilities in these areas
27

Data Analytics Engineer Resume Examples & Samples

  • Masters in Computer Science, Industrial Engineering, Operations Management, Management Information Systems, or a related field
  • 6+ years of experience in a relevant field
  • Strong problem-solving skills and ability to prioritize conflicting requirements
  • Excellent written and verbal communication skills and ability to succinctly summarize key findings
  • Comfortable working as both part of a high-performing, diverse team and as an independent performer
  • Ability to multitask and prioritize critical tasks and conflicting requirements with a high attention to detail
  • Strong PC skills, including Microsoft Excel, Word, Project
  • Good knowledge of SQL and working with relational databases
  • Knowledge of data visualization software (Microstrategy, Tableau)
  • Design and conduct rigorous experiments on the effectiveness and efficiency of different technologies that will inform long term strategy
  • Willingness to travel 15% of the year
  • Experience with Unix and Python/SQL scripting
  • Familiarity with distribution or fulfillment center operations, software/firmware development or database administration
  • Experience with big data and object oriented programming languages (Python, Ruby, Perl, Java, etc.)
  • Experience in data mining using databases in a business environment with large-scale, complex datasets
  • Experience using Cloud Storage and Computing technologies such as AWS RedShift, RDS, Hadoop etc
28

Data Analytics Engineer Resume Examples & Samples

  • Develop, maintain, support, debug and deploy software applications across Micron’s global manufacturing sites
  • Partner with manufacturing and engineering teams to define and direct data warehouse and analytics systems and solutions
  • Identify new data-source in the network that will create new insights to business needs
29

Data & Analytics Engineer Resume Examples & Samples

  • Build understanding of the data environment as well as analysis & reporting requirements as basis for a centralized data warehouse solution which enables data driven decision making in HR
  • Create detailed design for BI solutions in alignment with Roche BI landscape and bring conceptual design down to a level of detail that can be physically implemented
  • Analyse current challenges and review internal system capabilities to determine how to conduct operations more effectively
  • Be a thought partner to HR (Data) Analysts and our internal customers in providing solutions and ensuring that the solution landscape supports the delivery of simple standard reports up to advanced analytics
  • Collaborate with Software Developers, BI Engineers and Data Scientists to ensure that requirements for integration, security, data quality and cross functional usage are addressed
30

Senior Data Analytics Engineer Resume Examples & Samples

  • IoT reference cases where data analytics forms a part of the “whole” IoT solution
  • Enable data analytics solution capabilities internally, e.g. DA Lab and workbench
  • IoT customer project delivery with focus on data analytics
  • Demonstrated experience in successfully working cross-functional teams and integrations
  • Excellent written and oral communicator
  • Data analytics project skills in vertical industries are preferred
  • Demonstrated strong analytical and problem-solving skills
  • Ability to travel up to 25%, including international travel, on a regular basis
31

Senior Principal Big Data Analytics Engineer Resume Examples & Samples

  • Analyzes, designs, programs, debugs, and does ongoing modification of software components
  • Code may be used in commercial end-user applications, prototypes, or in test tools or other supporting programs
  • Using the required programming languages and other technologies, writes code, completes programming, and performs testing and debugging of applications
  • May interact with internal cross-functional members to better understand system requirements and/or necessary modifications
  • Responsible for the design, development, testing, documentation and analysis of modules or features of new or upgraded software systems and products
  • Develops and/or executes implementation according to project plans and priorities
  • May participate in development in any of a range of product areas such as thin client, rich client, server, installation, communication layers, and so forth
  • Reviews and provides suggestion on roadmap direction
  • Troubleshoot, analyze, replicate, regress and resolve complex field software problems escalated to engineering
  • Come up with solutions/implementations to consistently improve product stability, scalability, and performance
  • Design, implement and test, escalated enhancement feature requests to enhance functionality as needed with minimal risk to existing product stability, reliability and performance
  • Responsible for handling critical customer problems in real-time and developing code fixes or enhancements to be included in future code releases or patches
  • Coordinate, respond, track and follow-up on customer problem reports/technical support requests for Engineering. Craft sound technical plan of action for complex problems and execute them to resolution
  • Reproduce customer issues and resolve them by either establishing a workaround or a solution, or by debugging and creating a bug fix
  • Work with support engineers, professional services and sales engineers to investigate and handle customer and field escalated cases
  • Create and document best practices guidelines and knowledge base articles
  • Completes documentation and procedures for installation and maintenance
  • Provides estimated timelines for issues reported from the field
  • Ensures products are up to date with 3rd party components that are in use
  • Proactively identify non-compliance of code against requirements/standards/design and raise defects
  • Reviews design, architecture and implementation done by junior staff keeping in mind overall product impact
  • Provide technical leadership to the team
  • Direct interaction with customers and vendors
  • Strong software developer with minimum of 6 years of advanced Java programming building distributed, multi-threaded, scalable, highly available server applications
  • Experienced dealing with micro-services, REST APIs and protocols, Json and/or XML datasets
  • Experience building scalable SAAS applications in the cloud is plus
  • Scala programming knowledge and experience a huge plus
  • Linux OS and scripting experience required
  • Experience with one or more of these scalable distributed computing technologies like Akka, Cassandra, Spark, Hadoop is a huge plus
  • Experience with the AWS technologies like Kinesis, Dynamo, Redshift etc a huge plus
  • Experience with scripting technologies including bash, python, JavaScript and web technologies required
  • Knowledge of Machine learning, Spark ML, etc., is a plus
  • Use of Open Source and 3rd party products for integration into platform products required
  • Experience with Source control systems like Git
  • Experience with Jira, Clearquest and other issue tracking systems
  • Specialist with advanced skills in engineering tools, methods and processes
  • Ability to communicate complex information to internal and external audiences
  • Solves advanced or very complex technical problems of a broad nature
  • Works on extremely complex problems where analysis of situation or data requires an evaluation of intangible various factors
  • Provides the technical expertise and/or direction for multiple complex projects of a development or technology group
  • Develops project plans
  • Demonstrates technical flexibility, and creativity in problem solving
  • Ability to think strategically and influence a broad group
  • Strong customer service and teamwork skills
  • Independently works with management on a department-wide level
  • Partners with management team in developing tactical plans and objectives for the department and development for the company as a whole
  • Provides the technical expertise and/or direction to less experienced team members
  • Actively contributes to design or process development in a broad scope
  • Contributes to the design specification of a product
  • Experience in multi-threaded programing and object-oriented design
  • Experience with software debugging tools and techniques
  • Experience in advanced design concepts like Design Patterns
32

Lead Data & Analytics Engineer Resume Examples & Samples

  • Work with internal and external customers to capture data and analytics requirements
  • Assist in defining, gathering and analyses of development test vehicle and flight test vehicle data
  • Develop, verify, and validate analytics to address customer needs and opportunities
  • Rapid prototyping of analytic solutions
  • Robust approach to analytic verification and validation
  • Work to translate algorithms into commercially viable products and services
  • Perform exploratory and targeted data analyses using descriptive statistics and other methods
  • Perform data quality assessment, data cleansing and analytics
  • Generate reports, annotated code, and other projects artefacts to document and archive e.g. using version/source control systems
  • Communicate methods, findings, and outcomes including to key stakeholders
  • Engage across the global GE Aviation business, to ensure our Data Science approach is aligned and consistent with business needs
  • Deliver new and commercially re-usable analytics that meet quality standards to drive growth in asset, application & industry coverage that are targeted by GE businesses
  • Leverage strong engineering & analytics background to develop new analytics
  • Master’s Degree in a “STEM” subject (Science, Technology, Engineering, Mathematics) (or equivalent knowledge/experience) plus proven experience in analytics development for applications in a commercial/industrial setting OR Ph.D. in a “STEM” subject (Science, Technology, Engineering, Mathematics) (or equivalent knowledge/experience) plus some experience in analytics development for applications in a commercial/industrial setting
  • Highly proficient user of one or more of the following analytic software tools R, Matlab, Python
  • Demonstrable competence in SQL preferred
  • Strong engineering & analytics background
  • Experience / awareness of key technologies and concepts big data and analytics; Internet of Things; Industrial Internet; Cloud Services etc
33

Lead Advanced Data Analytics Engineer Resume Examples & Samples

  • 2 years of experience with advanced SQL
  • 2 years of advanced Unix / Linux skills
  • 2 years of experience with ETL and data movement tools
  • 2 years of experience with relational databases
  • 2 years of management experience
34

Data Analytics Engineer Resume Examples & Samples

  • Adopt a FastWorks mindset to support Business data and
  • Bachelor's Degree in Computer Science, Information
  • Primary role in recent positions must be as a Lead Data /
35

Tableau Developer / Data Analytics Engineer Resume Examples & Samples

  • Partnering with customers to document analytic requirements
  • Developing and testing analytic solutions in Tableau
  • Completing all efforts within schedule parameters
  • Demonstrated ability to work with customers to develop and deploy business analytics solutions
  • Demonstrated ability to apply data analytics concepts and methodologies to business requirements
  • Demonstrated experience with Tableau and other Business Intelligence products
  • Experience with SQL databases, ETL products, and data prep activities
  • Experience with in-memory databases, preferably SAP HANA
  • Experience successfully managing multiple tasks
36

Data Analytics Engineer Resume Examples & Samples

  • Working with the engineering team to make sure that we have the right data ingestion in place
  • Architecting data models that are reusable, scalable and performant
  • Managing and maintaining the ETL processes into our data warehouses
  • Building, testing, and deploying new data pipelines based on business requirements
  • Managing internal databases that analytics team uses for reporting and dashboarding needs
  • Supporting the analytics team with building and scheduling jobs to pull data from various APIs
  • Supporting the analytics team with developing interactive dashboards and reports, and managing the access control
37

Senior Data Analytics Engineer Resume Examples & Samples

  • Provides oversight for D3’s infrastructure technology and domains
  • Ensures D3’s analytic infrastructure systems are stable and performing correctly
  • Works closely with Allstate Data Scientists and other users to build a deep understanding of their current / future needs and is a strong advocate with Technology to ensure those needs are met
  • Works closely with key Technology partners to provide ongoing evaluation of infrastructure and services capabilities both on premise and in the cloud
  • Partners closely with peers in Allstate Technology teams to influence and shape the evolving strategic infrastructure needs aligned with desired business objectives
  • Works with Technology to stay current with emerging trends in systems development and delivery to ensure that the D3 organization uses the most appropriate platform / technologies
  • Engages in long-term technical planning and drives Infrastructure strategy and standards to meet D3’s advanced analytics needs in partnership with key Technology partners
  • Promotes technical standards, guidelines, Best Practices and quality control measures for enabling and implementing software systems in partnership with key Technology partners
  • Educates peers in D3 on standards, processes, and tools both within and external to research / experimentation zones
  • Partners with Technology and D3 Data Science teams to optimize operations through automation for code deployments, packaging and other repeatable tasks
  • Establishes test cases and scripts for validation and consistent operations following infrastructure and other changes
  • Develops and owns security policies for D3 in alignment with enterprise standards and our Technology partners (Including Firewall rules)
  • Create, manage, and own Docker / Domino images and strategy for D3
  • Bachelor’s or Master’s/MBA degree in a field such as Computer Science, Computer Engineering, Data Architecture, or equivalent skills
  • 10+ years of related experience or equivalent skills & ability
  • Working knowledge on current hardware especially for (distributed) numerical computation; this might include GPUs, FPGAs, Intel MIC, network layer, storage arrays, cluster file systems
  • Experience in analyzing / tuning performance of such computations (esp. multithread/multiprocess) is desired
  • Broad knowledge of advanced environment monitoring & management tools, performance modeling tools, capacity analysis tools, and other advanced modeling and trending tools in a distributed environment
  • Knowledge of UNIX System Administration and networking including working knowledge of TCP IP, DNS, HTTPS/SSL, load balancing etc
  • Working experience in server configuration management and virtual private cloud setups (esp. for distributed computing; example hipaa-compliant setups for sufficient data protection) and public cloud (AWS)
  • Knowledge of best practices related to security, performance, and disaster recovery
  • Advanced knowledge of professional standards and technology trends within the analytics industry
  • Demonstrated ability to work in an interdisciplinary team environment
  • Passion to learn new technologies and languages
  • If located in Bothell, WA or Menlo Park,CA, frequent travel to Northbrook, IL (suburban Chicago) required
38

Data Analytics Engineer Resume Examples & Samples

  • 4+ years of experience in areas related to data science, data analytics or data quality
  • Strong analytical and problem solving skills – with very good data manipulation capabilities
  • Intellectual curiosity. Consistently think out of the box, flexibly think around problems, iterate through possible solutions
  • Tolerance for ambiguity dealing with large and complex data sets
  • Perseverance, relentlessly driven to find the solutions when facing obstacles
  • Analytical experience using statistical methods
  • 3+ years of SQL (MS SQL, DB2) experience
  • Experience writing and optimizing advanced SQL queries with advanced experience pulling data from SQL database for analysis
  • Experience working with relational database structures, SQL and/or flat files and performing table joins, web crawling
  • Data exploration, attention to detail and ability to see the big picture
  • Ability to learn quickly and contribute ideas that make the team, processes and product better
  • Ability to communicate your ideas so that business analytics engineers and management can understand
  • Knowledge of techniques and tools that promote effective analysis and the ability to determine the root cause of problems and create alternative solutions that resolve the problems in the best interest of the business
  • Demonstrated experience working closely with customers and understanding their needs
  • Algorithmic thinker, ability to break down problems and recompose them in ways that are solvable
  • 2+ years of Python or Java development experience (familiarity with data science modules: Pandas, SciPy, NumPy, Matplotlib)
  • Unit testing, UML
  • Familiarity with JavaScript
  • Experience with the R statistical language
  • Ability to code and develop prototypes
  • Create efficient and clean code for reading by the team, apply PEP 8
  • A Github profile or public code portfolio
  • Proficiency in data quality
  • Experience debugging and tracing SQL performance issues
  • Experience designing, integrating,and optimizing distributed data processing pipelines
  • Experience with Tableau for data visualizations
  • Design, build and launch extremely efficient & reliable data pipelines to move data
  • Experience in Agile Kanban or Scrum
39

Chemometrics Data Analytics Engineer Resume Examples & Samples

  • Troubleshooting manufacturing process and quality problems by incorporating chemistry and engineering knowledge into multivariate data analysis
  • Consultation with internal Dow manufacturing clients to define and meet their needs in multivariate statistical data analysis to improve process and product quality
  • Performing research and leveraging emerging technology in multivariate statistical analysis into Dow
  • Work effectively as a team member in a self-directed team environment globally
  • Translate and communicate statistical results to non-statistics experts
  • Demonstrate leadership skills and actively participate in team meetings
  • Overcome obstacles (capital, resources, time) to achieve results
  • Be self-driven to actively generate, pursue and complete projects
  • Identify value-creation opportunities to apply chemometrics
  • Be interested and effective in learning new data analysis techniques through internal research collaboration,workshop, and journal reading
  • Be able to recognize opportunities and interact directly with clients to deliver effective solutions
  • Prioritize multiple projects and effectively allocate resources to maximize value creation
  • Possess strong verbal and written communication skills, including technical writing and presentation
  • Two years of experience using chemometric techniques (such as PCA, PLS) applied to manufacturing data in an industrial or academic setting is required
  • Industrial experience in the form of an internship
40

Data Analytics Engineer Resume Examples & Samples

  • 2-3 years experience building ETL processes for a multi-terabyte enterprise data warehouse
  • Strong grasp of data warehouse concepts and data models
  • Deep experience with at least one RDBMS platform, and advanced SQL skills in at least one dialect (Oracle, Teradata, MySQL, etc.)
  • Working knowledge of at least one analytics-related language (Python/R/Matlab)
  • Experience with at least one BI reporting tool (Tableau, MicroStrategy, Business Objects, Pentaho, etc.)
  • Exceptional oral and written communication skills
41

Senior Data Analytics Engineer Resume Examples & Samples

  • Degree qualified in STEM (Science, Technology, Engineering and Math) or equivalent knowledge and experience
  • Proven experience on modelling dynamic physical systems: mechanical, hydraulic, thermodynamic, electrical, etc
  • Competent in engineering mathematics with expertise in numerical methods, mathematical modelling and software development lifecycle
  • Good understanding of production engineering concepts (in particular: flow assurance, fluid dynamics, phase equilibrium)
  • Strong background in closed loop control theory and expertise in object oriented software design
  • Experience coding in one or more languages including Python, Matlab, Fortran, and C#. Experience in.NET would be beneficial
  • Good knowledge of subsea controls & instrumentation systems
  • Good understanding of optimisation theory for non-linear systems and optimisation filters
  • Subsea Oil & Gas experience would be beneficial
  • Be able to influence from both a strategic and technical standpoint across the function and business. Ability to influence at the peer and senior leadership level is critical
  • Knowledge of engineering analysis methods, mechanical & electrical systems, software systems, and advanced analytics methods (machine learning, advanced statistics, optimization, estimation, etc.)
  • Experience incorporating engineering analytics or advanced data-driven analytics into software solutions
  • Strong problem solving abilities
  • Strong customer mindset
  • Ability to work to tight deadlines and cope under pressure
  • Exceptional written, verbal communication, and presentation skills
42

Data Analytics Engineer Resume Examples & Samples

  • A successful candidate will install, configure, and manage information system hardware related to high-performance data analytics processing based on Linux systems
  • A successful candidate will also troubleshoot and resolve hardware and software problems related to server hardware, networking equipment, storage devices, and power and facilities interfaces
  • Working experience with Linux systems in a data center environment is essential, as well as experience with Ethernet networking, including defining and configuring VLANs, IP subnets, network virtualization, and network troubleshooting using open source diagnostic tools
  • Position will manage a variety of direct-attach and network storage systems in Linux environments
  • The successful candidate will use Puppet, Ansible or similar configuration management and automation frameworks
  • The position will be with deploying and managing analytics workload processing systems using Apache software projects such as Hadoop, Spark, Ambari, and MongoDB
  • The position will also use Cloud orchestration and automation tools such as OpenStack
  • The position is on a large team and will be supporting the services for a large customer
  • Requires Bachelor’s degree in Computer Science, Engineering, Mathematics, Management of Information Systems, or relevant discipline, or equivalent experience with the required technologies in the following section (4 years)
  • Minimum of 3 years’ experience in the following technologies
  • Red Hat Linux or Red Hat derivative distributions
  • Ubuntu Linux or Debian derivative distributions
  • Ethernet networking in scaled systems
  • Parallel or distributed file systems
  • Distributed configuration management frameworks
  • Distributed documentation and issue tracking systems
  • Outstanding written and verbal communication skills including strong interpersonal skills
  • Must be able to obtain and maintain a DOE Q and SCI level clearance which may require a polygraph test
  • Can start uncleared but must be able to start the clearance process upon acceptance
  • OpenStack
  • Data center facilities operations
  • Infiniband networking
  • Hadoop, Spark, and additional Apache analytics stack projects
  • Database system deployment and management
  • Ceph file system
  • Swift, S3 or similar object storage systems
  • Git software development tracking and management
  • An active Q or TS along with SCI security clearance
43

Data Analytics Engineer Resume Examples & Samples

  • Undergraduate or master’s degree and an excellent academic record required
  • 1 – 3 years of work experience after completing your undergraduate degree
  • 5+ years of Enterprise software development experience
  • 2+ years of cloud development experience
  • Working knowledge of ETL processes and strategies
  • Working knowledge of building and consuming web services
  • Advanced understanding/coursework in database management and math (Linear Algebra, Calculus)
  • Intellectual curiosity, along with excellent problem-solving skills, including the ability to disaggregate issues, identify root causes and recommend solutions
  • Ability to independently own front-end tool development and decisions, balancing demands and deadlines
  • Position requires ability to travel 30-50%
44

SDN NFV Data Analytics Engineer Resume Examples & Samples

  • Understanding of Big Data Analytics, AI and Machine Learning technologies to enable proactive automation solutions
  • A deep understanding of Datacenter virtualization technologies (servers, networks and software stacks), monitoring tools and processes
  • Analysis and development of new operational procedures leveraging all of the benefits of an SDN-enabled environment
  • Manage cross-functional teams across wireline & wireless organizations to build consensus on approaches for managing the transition to new, more efficient operational models
  • Develop and manage documentation covering all operational changes and transition plans envisioned for all targeted SDN-enabled platforms
  • Engage both the internal and external program management teams to develop network strategy and robust plans for component and application level transition to an SDN operations model
  • Proven ability to shape transformation strategies and drive innovative thinking
45

Big Data Analytics Engineer Resume Examples & Samples

  • Big Data Analytical Tools engineering - install, validate, test, and package analytical tools on Red Hat Linux and Wintel platforms
  • Publish and enforce Big Data Analytics Tools best practices, configuration recommendations, etc
  • Create and publish design documents, usage patterns, and cookbooks for user community
  • Partner with Citi sectors to solution analytical needs to large scale data problems
  • Perform security and compliance assessment for Big Data Analytical Tools
46

Data Analytics Engineer Resume Examples & Samples

  • 5+ years of experience in relational data bases, data structures, and queries
  • 2+ years of experience in big data analysis and tools (Hadoop, Spark, Drill, etc..)
  • UNIX/Linux systems
  • Project Management experience including planning, development, defect management, and status reporting
47

Data Analytics Engineer Resume Examples & Samples

  • Education: Bachelor's or Master's degree in an engineering or science discipline such as Computer Science, Computer Engineering, Data Analytics, Statistics, Mathematics, Electrical Engineering, Mechanical Engineering, Chemical Engineering and etc
  • Up to 2 years experience in a role related to data analytics, data science algorithms implementation, computer programming and/or software development and optimization (Preferred experience related to advanced analytics and tools discipline)
  • Programming skills: Highly proficient in R and Python
  • Knowledge in applied statistics
  • Ability to conduct training on software tools applications
  • Self-starter. Ability to drive initiatives and influence. Ability to work alone as well as in a team environment
  • Collaborative attitude and a global mindset with an ability to work well with native and non-native English speakers
  • Proficiency in English (oral and written)
  • Able to travel up to ~25%, including international
  • Able to participate in conference calls outside of regular local work hours
48

Senior / Lead Data Analytics Engineer Resume Examples & Samples

  • Implements solutions to complex problems using Machine Learning and Optimization Algorithms
  • Establishes customer-focused analytics capabilities through visioning, leadership, and mentoring
  • Discovers opportunities to improve systems, processes and enterprises through data analytics
  • Generates reports for decision-making using data visualization and data mining
  • Leads innovation by applying data analysis skill sets to develop cutting edge cold-chain solutions
  • Participates in the development of compressors and systems to improve reliability, cost and customer value
  • Establishes and maintains collaboration with other internal teams to apply cloud and edge-computing capabilities for the application of production and proprietary algorithms
  • Develops key understanding of the cold chain (develops domain knowledge)
  • Reads and understands algorithms and other techniques from academic papers
49

Data Analytics Engineer Resume Examples & Samples

  • Large scale data processing & modeling
  • Systems integration
  • MS or PhD in mathematics, physics or computer science required
  • Experience with application programming and software development using Java, Python, Ruby, Perl, Bash and other common languages
  • Experience with ensuring data consistency, discoverability, and quality
  • Experience with machine learning and statistical analysis
  • PhD in Physics or Computer Science preferred
  • Experience with JVM-based languages (Java EE, Scala, Clojure)
  • Experience with big data analytics platforms (Hadoop, Map Reduce, Hive, Pig), workflows (Oozie, cascading, scalding), databases (HBase, Accumulo, Mongo) and data serialization (Avro, thrift, xml)
50

Big Data Analytics Engineer, Junior Resume Examples & Samples

  • 1+ years of experience with performing systems administration in Windows, Linux, or VMware environments, including installation and configuration, monitoring system performance and availability, performing upgrades, using scripting languages to automate tasks and manipulate data, and troubleshooting
  • Experience in developing with a third–generation programming language
  • Knowledge of enterprise logging, including application logging and regular expressions
  • Knowledge of predictive modeling techniques
  • Experience with designing, implementing, configuring, and operating Splunk
  • Experience with Python and Java
  • Experience with Hadoop ecosystem and tools, including Storm, Spark, Accumulo and HBASE, or a variant NoSQL database
  • Experience with statistical software, including SAS, MatLab, and R
  • Experience with enterprise–scale operations and maintenance environments
  • Experience with working in a large enterprise environment and integrating solutions for a multi–vendor environment
  • Knowledge of federal information security policies, standards, procedures, directives, frameworks, federal security authorizations, assessment, and risk management processes for enterprise systems
  • Splunk Architect, Admin, and Splunk Power User Certifications
  • CISSP, Security+, or a related Certification
51

CDI Data Analytics Engineer Resume Examples & Samples

  • Bachelor's Degree in Computer Science, Information Systems or HS Diploma/GED with IT experience
  • Strong experience in metrics analysis
  • Knowledge of SLA, SLO, VOC, NPS and other metrics and KPI for end user support services
  • Familiar with Tableau, Sisense, Domo, and any other Business Intelligence software/platform, and visualization layer
  • Ability to work both autonomously and in constant collaboration with product owners, operations, and end users
  • Ability to clearly communicate data through both verbal and written communications such as presentations, dashboards, and email updates
  • Excellent organizational, interpersonal and written communication skills are a must
  • Able to successfully interact with all levels of the organization
  • Experience in analytical understanding of operational metrics related to support management
  • Strong work ethic & desire to learn
  • Spanish & French is a plus
  • Experience working in a global atmosphere
  • Knowledge and experience with ServiceNow
  • Demonstrated ability to drive results in a dynamic and fast pace environment
  • Drives change initiatives & strategies
52

Lead Data Analytics Engineer Resume Examples & Samples

  • More than 5 years software development experience
  • Ability to lead and architect data modeling, to help predict areas for SW improvement
  • Proven experience with Modeling and Simulation tools
  • Proficient in R or Similar Statistical Package is a plus
  • Understanding of high scale SW development models
  • Operations Research Background
  • Data Science Certification
  • Advanced Degree in related field: Business Administration, Statistics, Computer
53

Data Analytics Engineer Resume Examples & Samples

  • 5+ years of programming/scripting experience (e.g. Java, Python, R)
  • Prior experience with data cleaning, visualization, & reporting
  • Good understanding of Data mining & Machine learning techniques
  • Knowledge of SQL databases and database querying languages
  • Experience with Wireless technology is a plus
54

Big Data & Analytics Engineer Resume Examples & Samples

  • Work with business owners and development teams to define and develop data-driven applications and product prototypes
  • Gather data insights related to user behavior, product usage, audience segmentation, social media, quality of services, and media consumption to drive business decisions
  • Working with predictive analysts and data scientists, build scalable prototypes of machine learning algorithms, build production quality codes, manage and maintain the code base
  • Work with product management and internal stakeholders to help dictate the requirements and technical design of Fandango data services and related intelligence tools
  • Develop BI applications including transactional systems, mobile application development of BI products/services including Android, iOS, and/or cross platform
  • Contribute to every phase of the BI product development life cycle (design, development, testing, iteration, deployment)
  • Master's degree in CS, MIS, Statistics, Machine Learning, Applied Mathematics, Data Mining or a related field
  • Proven track record working on distributed, scalable, service-oriented platforms. Proven ability to deliver high quality, production ready code
  • 3+ years hands-on experience with Hadoop eco-systems (Hive, Pig, Spark, etc.)
  • 3+ years of experience in programming languages Python, Java, Scala, etc
  • 3+ years of experience in data extraction, data-driven statistical modeling, analysis and supervised learning using modeling languages such as R, Stata, MATLAB, etc
  • Experience in using Cloud services such as Amazon Web Services, Microsoft, IBM and Google Cloud
  • Experience in Machine Learning/Deep Learning APIs, frameworks, and AI tools
  • Experience with BI reporting tools (Tableau, MicroStrategy, SAP BusinessObjects, SSRS, etc.)
  • Excellent knowledge and expertise with SQL and Relational/Multi-dimensional Databases
  • Understanding of data warehousing concepts
  • Must maintain regular and acceptable attendance at such level as is determined at the company’s sole discretion
  • Must be available and willing to work extended hours (during crunch times!) per day including occasional weekends and holidays
55

Data Analytics Engineer Resume Examples & Samples

  • Conduct research and development based on current trends and technologies related to the data engineering and architecture, data security/governance, and related topics
  • Work with developers to build data pipelines, ETL processes , data solutions according to customer requirements and drive the entire deliverables accordingly
  • 5+ years in client facing roles with good understanding of data architecture, ETL and BI solutions etc
  • Hands on experience with few of the tools like Hive, pig, sqoop, oozie, Kafka, Nifi, Impala, Scala, spark streaming etc
  • Prior experience with R, Python is a plus
  • Hadoop administration skills is a plus
  • Experience with NoSQL database like Cassandra, MongoDB, NuoDB, Couchbase, HBase, Redis is a plus
  • Experience with various technology platforms, application architecture, design, and delivery including experience architecting large big data enterprise data lake projects
  • Strong written, verbal, and presentation skills
56

Data Analytics Engineer Resume Examples & Samples

  • Identify and apply appropriate algorithms and tools to discover patterns
  • Develop and perform experimental design approaches to validate findings or test hypotheses
  • Develop and deploy software required to successfully execute a data analysis project
  • Present and depict the rationale of the findings in easy to understand terms for the business
  • Work with building system domain experts and customers to assess needs and solve problems through the application of data analytics and associated technologies in an agile manner