The Golden State Warriors are seeking a Data Engineer to join our growing team. This is a full-time remote position based in San Francisco, California, United States and offers substantial influence over our data pipelines and data warehouse, in collaboration with data science and analytics teams. The role is essential to our daily data operations, particularly during the NBA season, and requires a proactive approach to data operations. You will contribute to batch and streaming data pipelines, data modeling and transformation for analytics, and the deployment of predictive models into production. You will also implement data validation and quality checks across pipeline stages and manage pipelines during in-season operations. Responsibilities include developing batch and streaming pipelines, data modeling and transformation for analytics and reporting, deploying predictive models, implementing data quality checks, and maintaining pipelines during in-season operations. Additional duties may be assigned. Required experience and skills include 4+ years in data engineering or similar, 3+ years in data operations or on-call roles, strong Python and SQL, experience with scalable ETL/ELT, and familiarity with orchestration tools such as Airflow or Dagster, transformation tools like dbt, and cloud providers like GCP or AWS. Git proficiency, excellent communication with technical and non-technical stakeholders, and the ability to influence partners are essential. Candidates should be able to balance multiple projects in a fast-paced environment and have a strong passion for sports

The Golden State Warriors are seeking a Data Engineer to join our growing team. This is a full-time remote position based in San Francisco, California, United States and offers substantial influence over our data pipelines and data warehouse, in collaboration with data science and analytics teams. The role is essential to our daily data operations, particularly during the NBA season, and requires a proactive approach to data operations. You will contribute to batch and streaming data pipelines, data modeling and transformation for analytics, and the deployment of predictive models into production. You will also implement data validation and quality checks across pipeline stages and manage pipelines during in-season operations. Responsibilities include developing batch and streaming pipelines, data modeling and transformation for analytics and reporting, deploying predictive models, implementing data quality checks, and maintaining pipelines during in-season operations. Additional duties may be assigned. Required experience and skills include 4+ years in data engineering or similar, 3+ years in data operations or on-call roles, strong Python and SQL, experience with scalable ETL/ELT, and familiarity with orchestration tools such as Airflow or Dagster, transformation tools like dbt, and cloud providers like GCP or AWS. Git proficiency, excellent communication with technical and non-technical stakeholders, and the ability to influence partners are essential. Candidates should be able to balance multiple projects in a fast-paced environment and have a strong passion for sports