Sr. Site Reliability Engineer - GM Motorsports in Concord

We are hiring a Senior Site Reliability Engineer (SRE) to join the GM Motorsports Software Engineering Data Platform team. This team builds and operates the next-generation data infrastructure that powers analytics, simulation, and telemetry insights across GM’s racing programs including Formula 1, NASCAR, IndyCar, and IMSA.

As a foundational member of the reliability function within the Data Engineering organization, you will ensure the availability, performance, and resilience of high-throughput telemetry and analytics platforms that ingest, process, and deliver mission-critical motorsports data. Our environment handles high-frequency streaming telemetry, simulation outputs, and engineering datasets that must be reliable, observable, and scalable. You will play a key role in designing systems where resilience, automation, and observability are built in from the start. We are looking for engineers who are uncomfortable with manual toil and are driven to build platforms where scaling, recovery, and operational insight are inherent properties of the system architecture.

What You’ll Do

• Platform Reliability: Design and implement reliability practices across the motorsports data platform, including Service Level Indicators (SLIs), Service Level Objectives (SLOs), and error budgets for streaming and analytics workloads.
• Streaming & Data Pipeline Resilience: Ensure reliability and performance of high-throughput streaming and batch data pipelines supporting telemetry ingestion, analytics processing, and simulation workloads using technologies such as Kafka, Flink, and Databricks.
• Observability & Incident Response: Build and maintain comprehensive observability frameworks including metrics, logs, and tracing across the platform. Develop dashboards, alerts, and automated responses that detect system degradation before it impacts engineering workflows.
• Infrastructure Automation: Drive the automation of platform infrastructure using Infrastructure as Code (IaC) and platform engineering best practices to enable consistent, reproducible environments across development, testing, and production.
• Operational Excellence: Identify operational friction and eliminate manual processes by implementing self-healing infrastructure, automation frameworks, and developer self-service capabilities.
• Data Platform Stability: Own the reliability of data ingestion, transformation, and storage layers, ensuring stable and performant integration across distributed data systems.
• Performance Optimization: Continuously evaluate platform performance and scalability, ensuring the data platform can support high-frequency telemetry ingestion, real-time analytics, and large-scale historical analysis.
• Mentorship & Technical Leadership: Provide mentorship and peer review to engineers across the platform team, promoting strong operational discipline, resilient system design, and high-quality engineering practices.

Your Skills & Abilities (Required Qualifications)

• Proven experience in Site Reliability Engineering (SRE), DevOps, or Platform Engineering supporting large-scale distributed systems.
• Strong experience with Linux systems administration and cloud-native infrastructure.
• Experience operating high-throughput data platforms or streaming systems (Kafka, Flink, Spark, etc.).
• Hands-on experience with Infrastructure as Code tools such as Terraform or similar frameworks.
• Experience implementing observability stacks (Prometheus, Grafana, OpenTelemetry, Datadog, etc.).
• Strong debugging and troubleshooting skills across distributed systems.
• Ability to break down complex reliability challenges into clear, implementation-ready initiatives.
• A growth mindset and commitment to continuous learning in a fast-paced engineering environment.

What Will Give You a Competitive Edge (Preferred Qualifications)

• Experience supporting data engineering platforms or analytics infrastructure.
• Experience with Kubernetes and container orchestration platforms.
• Familiarity with stream processing frameworks (Apache Flink, Spark Streaming, etc.).
• Experience with real-time telemetry, simulation, or high-frequency data environments.
• Experience implementing reliability practices across multi-cloud or hybrid cloud platforms.

This role is categorized as hybrid. This means the selected candidate is expected to report to a specific location at least 3 times a week. This job may be eligible for relocation benefits.

GM does not provide immigration-related sponsorship for this role. Do not apply for this role if you will need GM immigration sponsorship now or in the future.

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Benefits Overview: From day one, we’re looking out for your well-being–at work and at home–so you can focus on realizing your ambitions.

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