Staff Data Engineer

🕒 June 10

🌲 North Carolina – Remote

🌲 North Carolina – Remote

💵 $216k / year

⏰ Full Time

🔴 Lead

🚰 Data Engineer

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Teamworks

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 2005

⚽ Sports

☁️ SaaS

🤖 Artificial Intelligence

💰 $235M Series F - Teamworks on 2025-06

Sports • SaaS • Artificial Intelligence

Teamworks is a SaaS "Operating System for Sports" that unifies communication, roster and personnel management, scheduling, performance, coaching, compliance, inventory, nutrition, and other operations for professional, collegiate, Olympic/NGB, and military/tactical teams. The platform centralizes workflows, file sharing, automated processes, and AI-driven analytics (Teamworks Intelligence) to inform talent acquisition, roster construction, athlete evaluation, and game strategy. Teamworks serves thousands of teams and hundreds of collegiate departments and professional organizations worldwide, helping organizations coordinate staff and athletes, streamline operations, and improve performance.

📋 Description

• Define the technical architecture and platform standards for our lakehouse on AWS: distributed cloud architecture, schema conventions, multi-tenant isolation, and integration design • Lead design and delivery of the production pipelines that consolidate performance and product data, and own data modeling for complex entities (time-series, hierarchical, multi-source) so the models serve products, analytics, and ML • Introduce just enough data governance, ownership, and stewardship to raise our data maturity, and lay the catalog and semantic-layer foundation that analytics, ML, and AI agents can reason over • Author and maintain the Data Platform playbook (reusable patterns, ADRs, runbooks, Terraform modules) with data quality and reliability built in, so product teams can self-serve new datasets and integrations • Lead delivery end to end, from requirements and planning through coordinating workstreams and translating status to senior leadership and non-technical partners • Mentor engineers across levels, raise the bar through design review and on-call ownership, and be the engineering voice shaping the platform roadmap

🎯 Requirements

• 10+ years of data engineering or related experience, with strong Python for pipelines, transformations, and platform tooling • Deep expertise designing, operating, and setting direction for lakehouse platforms (Delta Lake, Iceberg, or Hudi) and modern processing engines (Spark, Databricks, Trino, or Snowflake) at production scale, with the judgment to make the hard tradeoffs and troubleshoot them • Expert AWS and distributed cloud architecture experience (S3, IAM, Glue, EMR/Lambda, networking), fluent writing Terraform and the best practices for implementing those designs • Deep data modeling and schema design for complex entities (time-series, hierarchical, multi-source) in multi-tenant environments, across multiple systems you've built (warehouses, lakehouses, relational), plus proven integration standards across teams (event-driven, API, batch) • Track record of standing up or significantly maturing a data platform from ambiguous goals, including the organizational work of aligning leaders and teams and communicating decisions to senior and non-technical stakeholders through RFCs and ADRs • Familiarity with how data governance, ownership, and stewardship programs are introduced, and the judgment to apply just enough to raise data maturity without over-engineering it

🏖️ Benefits

• Offers Equity • Offers Bonus