This is where you come in. I need a Senior Data Engineer to help lead this platform strategy, design the patterns that other teams will adopt, and make sure the data foundation we're building can support cross-product analytics, GenAI features, and the AI agents that are becoming core to how our products work. The work is highly visible, complex, and directly tied to capabilities that will show up on the field for athletes and coaches.
The Role- Own the design, implementation, and operation of production data pipelines that consolidate performance data and product telemetry into our lakehouse
- Lead architecture and infrastructure decisions for our lakehouse platform on AWS, including IaC in Terraform, schema design, and multi-tenant isolation patterns
- Drive data modeling for complex entities like time-series performance data, hierarchical org structures, and multi-source athlete profiles
- Build and document the reusable patterns, runbooks, and Terraform modules that let other product teams self-serve new datasets and integrations
- Raise the bar on platform reliability through observability, on-call rotation ownership, and post-incident learning that reduces toil and cost over time
- Partner with product and engineering teams to evaluate and evolve the platform's technology stack as the business scales into new environments
- Participate in our on-call rotation
What I'm Looking ForWhat You Must Bring- 7+ years of data engineering or related experience, with strong Python proficiency for pipelines, transformations, and platform tooling
- Hands-on experience designing and operating lakehouse architectures (Delta Lake, Iceberg, or Hudi) and modern processing engines (Spark, Databricks, Trino, or Snowflake)
- Deep AWS experience (S3, IAM, Glue, EMR/Lambda, networking) with production-grade Infrastructure as Code in Terraform
- Strong data modeling and schema design skills, with experience modeling complex entities like time-series, hierarchical, or multi-source data, and designing integration patterns across products or systems (event-driven, API, batch) with attention to reliability and multi-tenant isolation
- Strong communicator who builds consensus across teams, writes RFCs and design specs, and values documentation as part of the craft
Even Better If- You've worked in the sports industry have intuition for modeling athlete and performance data
- You bring broader software engineering knowledge beyond data engineering and are fluent in integration patterns across systems
- You're AI-forward in your day-to-day, using tools like Claude or Cursor for spec-driven development, and you actively look for ways to apply AI in the SDLC and platform operations
Why This RoleTeamworks has grown through acquisition into one of the most interesting data positions in sports. The lakehouse you'll help build is what ties our data together across products, fuels our AI-powered features, and gives us a position in the industry no one else has. If you want to lead platform strategy with real organizational backing and see your work translate directly to outcomes on the field, this is that role.
