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 You'll work on the same stack and toward the same goals as our senior engineers, with scope calibrated to where you are now and clear room to grow into bigger ownership over time.
The Role- 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 I'm Looking ForWhat You Must Bring- 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
Even Better If- You've worked with Spark, Databricks, Trino, dbt, or Airflow in production
- You have exposure to lakehouse architectures (Delta, Iceberg, Hudi) or modern data observability tooling
- You've actively used AI tools (Claude, Cursor, Copilot) for spec-driven development, code, tests, or troubleshooting
- You have experience working with sports performance data or understand the nuances of modeling athletic datasets
- You have a Bachelor's Degree or higher in Computer Science
Why This RoleYou'll be building real production data infrastructure that customers, including professional teams, college programs, and military organizations, depend on every day. You'll learn fast alongside senior engineers who invest in mentorship and craft, with visible ownership of pipelines that matter from the first months in. This is a strong launching pad for an early-career engineer who wants to grow inside a meaningful platform buildout.
This role is not eligible for sponsorship at this time.
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