Senior Manager, Data Engineering - Motorsports

Overview

Lead the Motorsports Data Infrastructure and Data Science teams through their managers, owning the strategy and delivery of data, analytics, and AI/ML platforms behind GM Motorsports' racing programs. This is a leader-of-leaders role with a significant individual contributor component.

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, aligned 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.
• Partner closely with Competition Engineering, Vehicle Performance, Race Strategy, and technical partners to deliver customer-facing features.

What you'll need

• 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.

Nice to have

• Experience leading both software/data engineering and data science functions.
• Experience with motorsports, automotive, or high-performance engineering data, such as vehicle dynamics, simulation, or aero correlation.
• Experience with Databricks AI capabilities, including Mosaic AI, Vector Search, Feature Store, Model Serving, and Genie.
• GenAI/LLM application experience, including RAG, agents, and evaluation.
• Experience with cloud architectures in low-latency or bandwidth-constrained environments.
• Experience standing up new programs or scaling teams through rapid growth.

Details

• Remote role: the selected candidate may be based anywhere in the country of work and is not expected to report to a GM worksite unless directed by their manager.
• GM does not provide immigration-related sponsorship for this role.
• Relocation benefits are available for candidates who qualify under company policy.