Senior Manager, Data Engineering – Motorsports

General Motors

. Lead the Motorsports Data Infrastructure and Data Science managers and their teams .

Posted 10/13/2026full-timeRemote • North Carolina • United StatesSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in leading data engineering and data science teams, with a strong focus on integrating Azure Databricks and MLOps practices to deliver production-ready data platforms. Proficient in architecting data pipelines and platforms while ensuring data governance and security.

Highest-signal resume keywords

Azure Databricks ExpertiseMLOps ProductionizationData Pipeline ArchitectureTeam Leadership in Data EngineeringReal-Time Data Processing

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonSQLData EngineeringData ScienceMachine LearningCI/CDInfrastructure-as-CodeFeature EngineeringModel Lifecycle ManagementAutomated Testing

Soft Skills

CommunicationLeadershipProblem-SolvingCollaborationDeadline Management

Tools & Technologies

Azure Data ServicesDatabricksSparkDelta LakeUnity CatalogEvent HubsAKSKey VaultGitTerraform

Industry Keywords

MotorsportsAutomotive EngineeringHigh-Performance EngineeringTelemetry DataTime-Series DataAI/ML EnablementData GovernanceStreaming DataCompetition-Sensitive DataCloud Architectures

Tech Stack

Tools & technologies

AzureCloudPythonSparkSQLTerraformUnityVault

About the role

Key responsibilities & impact

Lead the Motorsports Data Infrastructure and Data Science managers and their teams
Integrate data engineering, software, and data science into one roadmap and operating model
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
Unify real-time and batch data pipelines processing telemetry, timing and scoring, and trackside data
Lead productionization of ML models across race programs using MLflow-based MLOps
Drive adoption of AI coding tools, assistant platforms, and software development best practices
Set engineering standards for CI/CD, Terraform, automated testing, data quality, observability, and SLOs
Protect competition-sensitive data through security, access control, and IP safeguards
Manage Azure and Databricks cost and capacity, vendor relationships, and partner relationships
Communicate strategy, progress, and trade-offs to Motorsports and GM senior leadership
Partner with Competition Engineering, Vehicle Performance, Race Strategy, and technical partners to deliver customer-facing features

Requirements

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, including Spark, Delta Lake, Unity Catalog, Workflows/DLT
Expertise with Azure data services, including ADLS, Event Hubs, AKS, and Key Vault
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
Experience with CI/CD, Git, and infrastructure-as-code
Ability to deliver under hard, deadline-driven schedules and explain complex topics to engineering and executive audiences
GM does not provide immigration-related sponsorship for this role; applicants must not require GM immigration sponsorship now or in the future
Preferred: Experience leading both software/data engineering and data science functions
Preferred: Experience with motorsports, automotive, or high-performance engineering data
Preferred: Experience with Databricks AI capabilities, including Mosaic AI, Vector Search, Feature Store, Model Serving, and Genie
Preferred: GenAI/LLM application experience, including RAG, agents, and evaluation
Preferred: Experience with cloud architectures in low-latency or bandwidth-constrained environments
Preferred: Experience standing up new programs or scaling teams through rapid growth

Benefits

Comp & perks

Relocation benefits are available for candidates who qualify under company policy
Benefits supporting employee well-being at work and at home
Reasonable accommodations for applicants with disabilities