Staff Data Engineer - GM Motorsports

Overview

Expert-level individual contributor who sets technical direction for complex Motorsports data engineering initiatives, including real-time data ingestion, telemetry, data quality, cloud platforms, and race-day operational systems.

What you'll do

• Set technical direction and develop target-state architecture for complex, cross-system data platforms and products.
• Lead large, high-visibility initiatives that integrate multiple teams, disciplines, technologies, and stakeholder needs.
• Design and implement innovative, scalable solutions for real-time ingestion, telemetry, event and session data, data quality, and analytical products.
• Exercise independent judgment to analyze complex problems, select appropriate methods, evaluate tradeoffs, and make durable technical decisions.
• Establish and own measurable technical and operational outcomes, including reliability, data quality, throughput, cycle time, recovery, and service-level performance.
• Develop standards, policies, methods, and reusable patterns for schemas, data contracts, observability, testing, deployment, security, and recovery.
• Lead technical planning, dependency management, risk identification, and sequencing for roadmap and race-critical work.
• Anticipate and escalate risks that could affect customers, race operations, delivery commitments, or functional outcomes, while providing actionable recommendations.
• Improve operational reliability through incident leadership, root-cause analysis, automation, runbooks, and permanent corrective actions.
• Influence adoption of new approaches through data, clear communication, persuasion, and collaboration across teams with differing priorities or practices.
• Serve as a technical resource and indirect leader by mentoring engineers, guiding design reviews, and raising engineering capability across the organization.
• Partner with stakeholders to understand customer and business needs and translate them into scalable data solutions.
• Champion change management and continuously improve engineering processes, tools, and ways of working.

What you'll need

• Deep expertise in data engineering, distributed systems, cloud platforms, and production software development.
• Demonstrated experience setting technical direction and delivering complex solutions spanning multiple teams or functional areas.
• Strong programming experience in Python, Java, Scala, or a comparable language.
• Experience designing and operating streaming and batch data pipelines at production scale.
• Strong knowledge of data modeling, schema evolution, data quality, observability, testing, deployment, and incident response.
• Demonstrated ability to work independently on ambiguous problems and make decisions with broad business and technical implications.
• Experience influencing stakeholders and gaining adoption of new architectures, processes, or technical practices without relying on direct authority.
• Strong communication, collaboration, technical writing, and mentoring skills.

Nice to have

• Experience with Databricks, Apache Kafka, Flink, Spark, Kubernetes, AWS, Azure, or comparable technologies.
• Experience with real-time telemetry, event processing, time-series data, or latency-sensitive production workloads.
• Experience supporting systems during high-availability or time-critical operating periods.
• Experience with data science, machine learning, analytics, or engineering strategy teams.
• Experience establishing engineering standards, technical communities of practice, or cross-functional architecture forums.
• Interest in motorsports, vehicle systems, race strategy, or performance engineering.

Details

• Remote role: candidate may be based anywhere in the United States and is not expected to report to a GM worksite unless directed by their manager.
• Salary range: 160K-180K, plus bonus potential under an incentive pay program.
• GM does not provide immigration-related sponsorship for this role.
• Relocation benefits are available for candidates who qualify under company policy.