Data Engineer

Title:Data Engineer, Basketball Data Strategy Department:Basketball Data Strategy, Basketball Operations Reports to:Senior Data Engineer, Data Systems Position Summary: The Data Engineer, Basketball Data Systems is a core contributor on the Basketball Data Systems team. Working under the direction of the team's senior engineers and data-systems leadership, they build, maintain, and operate the pipelines and serving datasets of a modern cloud data platform spanning ingestion, transformation, storage, and service layers across both batch and near‑real‑time (in-game) delivery, using statistical feeds from external vendors and internal sources. This position focuses on the hands‑on implementation and day-to-day reliability of that platform: building curated bronze, silver, and gold datasets to establish patterns and data contracts, materializing them into the serving layer for web and mobile products, running backfills, and keeping pipelines performant and well maintained. It works alongside the Data Science / Analyst teams to ensure the cleanliness, integrity, accuracy, and relevance of the data to be analyzed, and alongside the Software Development team to deliver data into performant products. It is an excellent opportunity for an engineer who wants to grow toward broader platform ownership while working in a greenfield cloud stack under experienced mentorship. Essential Functions (Duties & Responsibilities**): Build and maintain data pipelines: implement and operate automated bronze, silver, and gold pipelines that collect, clean, and transform data (structured and unstructured) from internal and third‑party sources, following the platform's established medallion patterns, schemas, and data contracts. Deliver the serving layer: build and maintain the gold data marts and the load that materializes them into the serving database (PostgreSQL), along with the serving views and tables that the web and mobile products read, to the shapes agreed with the Software Development team. Run backfills and reprocessing: execute idempotent historical backfills and routine reprocessing, validating outputs across seasons. Support live and in-game data flows: help build, operate, and monitor the incremental, near‑real‑time pipelines that deliver in-game data, applying the platform's idempotency and quality patterns under the event‑driven design the senior engineers set. Maintain and tune the lakehouse: perform table maintenance such as compaction and small‑file management, partitioning, and storage‑format upkeep to keep queries fast and costs controlled. Apply data‑quality controls: roll out and maintain the team's validation, quarantine, run‑ledger, and alerting seam across tables, including automated quality checks and unit testing of transformation logic. Contribute to the data catalog and lineage: help generate and maintain the machine‑readable table catalog (grain, columns, sensitivity, and dependencies) that documents the ecosystem and drives orchestration. Support new‑source onboarding: when scoped, land and shape new reference and entity sources, and assist with the ingestion and processing of player‑tracking and other high‑precision movement data. Partner with consumers: work alongside the Data Science / Analyst and Software Development teams as the primary users of these datasets, incorporating their feedback on usability and correctness. **Duties & Responsibilities subject to change based on organizational needs and direction from management. Education: Bachelor's in Statistics, Computer Science, Engineering, or a related field, or equivalent academic or professional experience; experience working with database solutions in a professional, best‑practices environment. Minimum Qualifications: 2 to 4 years of experience in a data engineering or similar role. Database skills: strong proficiency in SQL and relational database design (e.g. PostgreSQL, SQL Server), including a working knowledge of best practices such as normalization, indexing, and query optimization. Exposure to nonrelational stores (document, time‑series, or vector) is a plus. Cloud pipelines: experience building and maintaining data pipelines in a cloud environment; AWS preferred. Orchestration: experience with a workflow orchestration tool (e.g. Prefect, Airflow). Strong Python and SQL skills, with experience transforming data in Spark (PySpark) or a similar framework. Familiarity with columnar and lakehouse formats (e.g. Parquet, Iceberg) and working with large datasets; exposure to high‑precision location or movement data (sub‑second sampling) is a plus. Exposure to streaming or near‑real‑time data processing (e.g. microbatch, structured streaming, Kafka or Kinesis) is a plus. Comfort with version control and CI/CD; exposure to infrastructure‑as‑code and containers (e.g. Docker) is a plus. An interest in data quality and observability, and in treating data infrastructure as production software. Other Qualifications: A strong sense of organization High agency, with an eagerness to learn and grow under senior mentorship Adaptability and "outside-the-box" thinking Knowledge of and passion for NBA basketball Location:El Segundo (office M-F), and other occasional off‑site events Travel:Less than 5% of the time Hours:Full-time. Must be available to work evenings, weekends and holidays as reasonably required The pay range for this role is $120,000 - $130,000 annually. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to skill set, depth of experience and certifications. In addition to those factors, we consider the relative pay of our current employees in similar positions when making a final offer. We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, sexual orientation, age, disability, gender identity, marital or veteran status, or any other protected class. #J-18808-Ljbffr