Senior Manager, Data Engineering - Motorsports

# Senior Manager, Data Engineering - Motorsports Full time

Job Description

The Role GM Data Engineering is seeking a Senior Manager to lead the teams that build and operate the data, analytics, and AI/ML platforms behind GM Motorsports' racing programs across Formula 1, NASCAR, Indy Car, IMSA, and beyond. You will own the strategy and delivery a data infrastructure that turns high-frequency telemetry, simulation, aero, and trackside data into insights that race engineers and strategists trust, at the track, and between events.

This is a leader-of-leaders role with a significant individual contributor component. You will lead the Motorsports Data Infrastructure and Motorsports Data Science teams through their managers, and bring them together into a single delivery model for data platforms, strategy tools, and AI/ML. You will also stay hands-on as the senior technical authority: setting architecture, reviewing and writing production code, and tackling the hardest problems directly.

You will partner closely with Competition Engineering, Vehicle Performance, and Race Strategy, and technical partners to deliver customer facing features.### What You'll Do
* Lead and develop the Motorsports Data Infrastructure and Data Science managers and their teams, growing technical leaders and a shared culture of engineering excellence.
* Integrate data engineering, software, and data science into one roadmap and operating model, from raw telemetry through models and the strategy tools race engineers use.
* Contribute hands-on as the senior technical lead: architect pipelines and platforms, prototype ML and GenAI solutions, review code, and support critical issues during race weekends.
* Own the motorsports data platform roadmap, covering ingestion, streaming, lakehouse, governance, and AI/ML enablement, and align it to program priorities and the race calendar.
* Unify real-time and batch data pipelines into a cohesive platform processing telemetry, timing and scoring, and trackside data using Databricks, Delta Lake, Kafka/Event Hubs, and Spark/Flink streaming.
* Lead the productionization of ML models to drive a competitive edge across race programs using MLflow-based MLOps.
* Drive the adoption of AI coding tools, assistant platforms, and software development best practices across the engineering teams.
* Set engineering standards for CI/CD, Terraform, automated testing, data quality, observability, and SLOs on race-critical systems.
* Protect competition-sensitive data through security, access control, and IP safeguards across GM, race teams, and partners.
* Manage Azure and Databricks cost and capacity, along with vendor and partner relationships.
* Communicate strategy, progress, and trade-offs to Motorsports and GM senior leadership.### Your Skills & Abilities (Required Qualifications)
* Bachelor's degree in Computer Science, Engineering, Data Science, or a related field.
* 10+ years in data engineering, software engineering, or data science, delivering production distributed data platforms.
* 5+ years leading engineering or data science teams, including managing managers, while remaining an active technical contributor.
* Deep expertise with Azure Databricks (Spark, Delta Lake, Unity Catalog, Workflows/DLT) and Azure data services (ADLS, Event Hubs, AKS, Key Vault).
* A proven record of taking ML/AI into production, including feature engineering, model lifecycle, MLOps, and monitoring.
* Experience with real-time streaming and high-frequency time-series data.
* Strong Python and SQL skills, plus experience with CI/CD, Git, and infrastructure-as-code.
* The ability to deliver under hard, deadline-driven schedules and to explain complex topics to engineering and executive audiences.

What Will Give You a Competitive…