The Los Angeles Lakers are expanding their basketball operations division by opening a recruitment process for a Senior Data Engineer within their Basketball Data Strategy department, according to recent professional listings. The role targets experienced technical professionals to build, architect, and maintain modern cloud data platforms supporting the franchise’s analytical and on-court strategies.
Role Requirements and Technical Stack
According to the position summary published by the organization, the Senior Data Engineer will design end-to-end data infrastructure in a greenfield stack, reporting directly to the Director of Basketball Data Strategy. Candidates must possess expert-level proficiency in relational database design, including SQL Server, PostgreSQL, and Snowflake, alongside experience with nonrelational data structures such as document stores, time-series solutions, and vector storage.
The position requires a minimum of six years of experience in a similar technical role and a bachelor’s degree in statistics, computer science, engineering, or a related field. Qualified applicants are expected to demonstrate hands-on experience architecting data platforms with cloud platforms like Amazon Web Services (AWS), as well as proficiency in workflow tools like Apache Airflow for automated pipeline management.
Core Responsibilities in Basketball Data Strategy
The incoming engineer will oversee the franchise’s complete basketball data ecosystem. Responsibilities include ingesting and processing diverse data streams such as official National Basketball Association (NBA) statistics, non-NBA basketball data, player tracking feeds, health and wearables performance data, and natural language qualitative inputs like scouting reports.
Additional duties involve optimizing 3D tracking motion capture data ingestion for analytical use, establishing rigorous data validation frameworks, and leading platform migration efforts. The engineer will collaborate closely with the franchise’s data science, analyst, and software development teams to ensure production-grade datasets are fully validated and optimized for predictive modeling and web and mobile product delivery.
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