Senior Data Engineer

Teamworks

7d•$185,000 - $185,000

About The Position

Scott Roberts, Senior Manager, Engineering at Teamworks, is seeking a Senior Data Engineer to join his Data Platform team. This role is crucial for building the foundation that integrates athlete performance data, product telemetry, and acquired data sets into a modern lakehouse. The goal is to create a unified data system that supports cross-product analytics, GenAI features, and AI agents, with high visibility and direct impact on athletic and coaching capabilities.

Requirements

7+ years of data engineering or related experience
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

Nice To Haves

Experience in the sports industry with intuition for modeling athlete and performance data
Broader software engineering knowledge beyond data engineering and fluency in integration patterns across systems
AI-forward in day-to-day work, using tools like Claude or Cursor for spec-driven development, and actively looking for ways to apply AI in the SDLC and platform operations

Responsibilities

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