Remote Data Engineer - Production Pipelines and Analytics

Golden State Warriors; San Francisco (CA); On-site; USD 148,500 - 181,500; Full time

Benefits offered by this job

Medical, Dental & Vision

401K match

Vacation + PTO

Summer Half-Day Fridays

Parental leave

Warriors home tickets

Team store discount

Job summary

The Golden State Warriors are seeking a Data Engineer to shape our data pipelines and warehouse, collaborating with data science and analytics teams. This full-time remote role drives data operations, with a focus on reliable, scalable analytics during the NBA season.

You will develop batch and streaming pipelines, model data for analytics, and deploy predictive models while ensuring data quality and operational resilience across pipelines.

Qualifications

• 4+ years of data engineering or similar experience.
• 3+ years of data operations or on-call experience.
• Strong Python and SQL programming abilities.
• Experience writing scalable ETL/ELT processes.
• Experience with orchestration tools like Airflow or Dagster.
• Experience with transformation tools like dbt.
• Experience with cloud providers like GCP or AWS.
• Git proficiency and version control discipline.
• Strong written and verbal communication; ability to influence stakeholders.

Responsibilities

• Develop batch and streaming data pipelines and event-driven workflows.
• Model data and transform it for analytics and reporting.
• Deploy predictive models into production.
• Implement data validation and quality checks across pipeline stages.
• Manage data pipelines during in-season operations and incidents.
• Collaborate with data science, analytics, and business partners.

Skills

Python programming

SQL

ETL/ELT

Airflow

Dagster

dbt

GCP

AWS

Git

Stakeholder communication

Job description

The Golden State Warriors are seeking a Data Engineer to shape our data pipelines and warehouse, collaborating with data science and analytics teams. This full-time remote role drives data operations, with a focus on reliable, scalable analytics during the NBA season.

You will develop batch and streaming pipelines, model data for analytics, and deploy predictive models while ensuring data quality and operational resilience across pipelines.