Staff Data Engineer - GM Motorsports
About The Position
The Staff Data Engineer is an expert-level individual contributor who sets technical direction for complex Motorsports data engineering initiatives. Working independently with broad latitude, the role applies deep expertise and sound judgment to ambiguous problems and delivers solutions with measurable impact across teams and functional areas. The role leads architecture and engineering practices for real-time data ingestion, telemetry, data quality, cloud platforms, and race-day operational systems. It influences technical decisions across the organization, mentors engineers, and partners with engineering, data science, platform, product, and racing stakeholders to deliver durable business outcomes. The position is expected to act as a recognized subject-matter expert, lead initiatives with cross-functional visibility, set objectives for technical and operational results, and contribute measurably to functional outcomes. The role is categorized as remote. 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. Relocation benefits are available to candidates who qualify under company policy.
Requirements
- 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 Haves
- 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.
Responsibilities
- Set technical direction and develop target-state architecture for complex, cross-system data platforms and products.
- Lead high-visibility initiatives integrating multiple teams, disciplines, technologies, and stakeholder needs.
- Design and implement scalable solutions for real-time ingestion, telemetry, event and session data, data quality, and analytical products.
- Analyze complex problems independently, 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 affecting customers, race operations, delivery commitments, or functional outcomes, and provide 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.
- Mentor engineers, guide design reviews, and raise 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.
- Demonstrate GM behaviors, including integrity, customer commitment, innovation, candid risk communication, urgency, inclusion, teamwork, and ownership of outcomes.
Benefits
- Medical, dental, and vision benefits
- Health Savings Account
- Flexible Spending Accounts
- Retirement savings plan
- Sickness and accident benefits
- Life insurance
- Paid vacation and holidays
- Tuition assistance programs
- Employee assistance program
- GM vehicle discounts
- Incentive pay program with payouts based on company performance, job level, and individual performance
- Relocation benefits for candidates who qualify under company policy
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
