Basketball Data Systems Engineer - Real-Time Pipelines

The Los Angeles Lakers; El Segundo (CA); On-site; USD 120,000 - 130,000; Full time

Job summary

The Los Angeles Lakers are seeking a Data Engineer for Basketball Data Strategy in El Segundo. You will build and maintain data pipelines, curate bronze/silver/gold datasets, and deliver serving data to web and mobile products, while ensuring data quality and reliability across batch and near-real-time streams.

Work closely with Data Science, Analytics, and Software teams to shape the data foundation and enable data-driven decisions in a greenfield cloud stack under mentorship.

Qualifications

• 2 to 4 years of experience in data engineering or a similar role.
• Strong SQL and relational database design, plus knowledge of normalization and indexing.
• Cloud pipelines experience; AWS preferred.
• Orchestration with a workflow tool such as Prefect or Airflow.
• Strong Python and SQL with Spark (PySpark) experience.

Responsibilities

• Build and maintain automated bronze, silver, and gold data pipelines.
• Deliver serving layer with gold data marts and PostgreSQL integration.
• Run idempotent backfills and routine reprocessing across seasons.
• Support near‑real‑time data flows and in‑game data delivery.
• Maintain lakehouse performance, partitioning, and storage formats.
• Apply data quality controls and automated validation checks.
• Contribute to data catalog and lineage documentation.
• Onboard new data sources and shape reference/entity data.
• Collaborate with Data Science/Analyst and Software Development teams.

Skills

SQL

Python

Spark (PySpark)

Airflow

Prefect

Docker

PostgreSQL

Data Pipelines

Cloud (AWS)

Data Quality

Education

Bachelor's in Statistics, Computer Science, Engineering, or related field

Tools

Airflow

Prefect

Kinesis

Job description

The Los Angeles Lakers are seeking a Data Engineer for Basketball Data Strategy in El Segundo. You will build and maintain data pipelines, curate bronze/silver/gold datasets, and deliver serving data to web and mobile products, while ensuring data quality and reliability across batch and near-real-time streams.

Work closely with Data Science, Analytics, and Software teams to shape the data foundation and enable data-driven decisions in a greenfield cloud stack under mentorship.