Data Engineer - GM Motorsports - General Motors LLC - Remote, OR Remote

Job Description

The Staff Data Engineer is an expert-level individual contributor who sets technical direction for complex Motorsports data engineering initiatives. This role works independently with broad latitude, applies deep expertise and sound judgment to ambiguous problems, and delivers solutions with measurable impact across teams and functional areas.

The role will lead architecture and engineering practices for real-time data ingestion, telemetry, data quality, cloud platforms, and race-day operational systems. The Staff Data Engineer will influence technical decisions across the organization, mentor engineers, and partner with engineering, data science, platform, product, and racing stakeholders to deliver durable business outcomes.

• 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 elevate 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.

• 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.

• Experience with Databricks, Apache Kafka, Flink, Spark, Kubernetes, AWS, Azure, or comparable technologies.
• Experience with real-time telemetry, event processing, time-series data,…