Data Engineer I

Teamworks

3d • $145,000 - $145,000 • Remote

About The Position

Scott Roberts, Senior Manager, Engineering at Teamworks, is leading the Data Platform team. They are building the lakehouse and data pipelines that consolidate performance data and product telemetry across athletic and tactical divisions. This role is at the build-and-ship layer and offers the opportunity to grow alongside the platform, working on the same stack and toward the same goals as senior engineers, with scope calibrated to the individual's current level and clear room for growth into bigger ownership over time.

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

Nice To Haves

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

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 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

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level