Head of Analytics Infrastructure EngBellevue, Washington
San Jose, California Requisition Number R0025893 Subsidiary eBay
eBay’s analytics infrastructure is one of the largest in the world, in particular among owned and operated private cloud environments. It houses data on customer behavior and financial transactions for eBay’s marketplaces globally. The environment includes traditional technologies such as relational data warehousing and an extract-transform-load (ETL) platform, as well as multiple Hadoop clusters, specialized variants of Hadoop such as Presto and Spark, and new eBay-developed technologies such as the Kylin analytical engine. It provides data for machine learning systems and for analytical reporting.
The team includes operations, software engineering, and quality engineering for the entire analytics data environment. Recruiting talented technologists to this team and supporting the career development of the current team members will be the top priority for the new leader. He or she will define eBay’s technology direction for analytics data infrastructure, will execute on that strategy, grow and develop the team, and influence and collaborate with stakeholders throughout the company. The leader will be expected to keep current on a variety of technologies--open-source and commercial, public cloud and private hyper-scale, real-time and batch mode--and exercise excellent judgment in whether, when and how to adopt these technologies for eBay’s needs.
Because of the intense demand and high cost of analytical environments, the leader of this team will also be accountable for responsible utilization of hardware, working closely with the hardware engineering team to understand and remove bottlenecks, and working closely with customers and finance teams to allocate resources to the greatest business need. Due to the high value of the data in the environment, he or she will need to collaborate with security and privacy teams to ensure proper documentation, access control, and compliance.
Graduate degree in computer science or closely related field
Very solid understanding of computer science fundamentals
Experience implementing data analytics systems, such as Hadoop
Deep understanding of relational databases and extract-transform-load (ETL) technology
Experience with high-availability operations
Familiarity with privacy and security controls in analytics environments
Experience with external technology partnerships and negotiations
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