Data Engineer I

About the role

I'm Scott Roberts, Senior Manager, Engineering at Teamworks, and I lead the Data Platform team. We're building the lakehouse and data pipelines that consolidate performance data and product telemetry across athletic and tactical divisions, the connective tissue behind cross-product analytics, GenAI features, and customer-facing insights. There's meaningful work to own from day one, and I'm hiring a Data Engineer to join us at the build-and-ship layer and grow alongside the platform.

Responsibilities

• Build and maintain production data pipelines that move performance and product data into the lakehouse with documented schemas, tests, and observability
• Contribute to platform code and Terraform-based infrastructure under the guidance of senior engineers, applying standard patterns and best practices
• Partner with product engineering and domain SMEs to design schema conventions and integrate new data sources cleanly
• Take ownership of components you build, including rotating on-call coverage, responding within Service Level Objectives (SLOs), and contributing runbooks and post-incident learnings
• Anticipate where pipelines can break, build in graceful failure handling, and raise reliability for the components you own

Requirements

• 2+ years of professional experience in data engineering, software engineering, or a closely related role building production systems
• Hands-on experience writing and shipping production-quality Python code, with a track record of code that's been reviewed, tested, and deployed
• Working knowledge of SQL and modern data warehouse or lakehouse concepts (e.g., Snowflake, Databricks, BigQuery, Redshift, Delta Lake, Iceberg)
• Exposure to AWS and willingness to grow into infrastructure-as-code practices using Terraform
• Strong troubleshooting instincts and clear judgment on when to ask for help vs. push through
• Comfortable participating in a rotating on-call schedule

Qualifications

• Exposure to Spark, Databricks, Trino, dbt, or Airflow in production
• Experience working with lakehouse architectures (Delta, Iceberg, Hudi) or modern data observability tooling
• Active use of AI tools (Claude, Cursor, Copilot) for spec-driven development, code, tests, or troubleshooting
• Experience working with sports performance data or understanding the nuances of modeling athletic datasets
• Bachelor's Degree or higher in Computer Science

Skills

• Python programming
• SQL and data warehousing concepts
• AWS and Terraform
• Data pipeline design and implementation
• Collaboration with product engineering and domain experts
• On-call rotation and incident response
• AI and machine learning integration
• Performance data analysis and modeling

Benefits

• Rotating on-call schedule
• Visible ownership of critical data pipelines
• Mentorship from experienced engineers
• Opportunities for growth and advancement

Pay

$145K

Schedule

Full-time