Sr. Site Reliability Engineer - GM Motorsports

General MotorsPort Charlotte, FL
14hHybrid

About The Position

The Role 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.

Requirements

  • 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.

Nice To Haves

  • 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.

Responsibilities

  • 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.

Benefits

  • From day one, we're looking out for your well-being–at work and at home–so you can focus on realizing your ambitions. Learn how GM supports a rewarding career that rewards you personally by visiting Total Rewards resources.

Stand Out From the Crowd

Upload your resume and get instant feedback on how well it matches this job.

Upload and Match Resume

What This Job Offers

Job Type

Full-time

Career Level

Mid Level

Education Level

No Education Listed

Number of Employees

5,001-10,000 employees

© 2024 Teal Labs, Inc
Privacy PolicyTerms of Service