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Big Data Engineer, Intermediate
Yahoo!
Sunnyvale, CA, United States
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Description
A Little About Us
Yahoo generates huge amount of data across various properties every day and it is critical to collect, manage and process user data at petabyte scale to provide timely and accurate user insights to enable Yahoo to deliver deeply personalized content and relevant ads. URS is the centralized repository of user knowledge and related services to enable easy user profiling and experimentation.
A Lot About You
We're looking for world-class, fun-loving engineers to join our team where you will have the opportunity to help developing the geo solutions from data collection, large scale data manipulation to long term data storage and low-latency retrieval systems. We seek engineers who have worked at Yahoo’s scale of 100s of Millions of users, 1000s of queries or requests per second with peaks far in excess of that, and all within milliseconds. You need to be self-driven, detail oriented, believe in teamwork, possess excellent communication skills and has the ability to multi-task.
Your Day
• Design and build fault-tolerant, high-performance, scalable, operable next generation platform components to solve complex problems and use cases.
• Work with the architects and senior engineers to Influence architecture, design and implementation.
• Maintain coding and documentation standards, participate in code reviews, and be a critical member of the Yahoo engineering team
• Work closely with product and management teams in influencing priorities
• Actively participate in the agile development process and design meetings to drive operability requirements for the system.
You Must Have
• BS/MS in Computer Science or related major
• Industry experience in big data technologies (e.g., Map/Reduce, Pig, Hive, HBase, Storm, Kafka, or Oozie)
• Strong fundamentals: data structures and algorithms
• 1-2 years of industry experience and high proficiency with OO languages like C++/Java is preferred
• Experience working in an Unix environment
• Experience working on high volume/high scale systems.
• Experience with machine learning algorithms and/or statistical methods is a big plus