Data Engineer
GM Performance Power Units
- Location
- Concord, NC
- Work style
- On-site
- Job type
- Other
- Posted
- Nov 1
- Today
Career path
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About the company
GM Performance Power Units
2 to 10 employees
At GM Performance Power Units, we are developing a new era of performance for the Formula 1 grid. Joining us means entering a startup racing environment backed by a legacy of engineering excellence, giving you the rare opportunity to help build a world-class program from day one.
What you'll do
- Build and maintain ingestion pipelines for agreed dyno, test rig, instrumentation and performance sources. Support batch, file and streaming patterns where requirements justify them.
- Preserve source files and relevant timestamps, units, calibration references, run identifiers and acquisition context. Implement validation and make missing or disputed context visible.
- Develop documented datasets and processing pipelines using Python and SQL. Implement duplicate prevention, late-data handling, checkpoints and controlled replay.
- Link test runs to approved engine, build and serialize component identities. Work with system owners to resolve mismatches and maintain traceable mappings.
- Prepare and publish agreed test and performance summaries from the AWS environment for use by the business and manufacturing data platform. Work with the business & manufacturing data engineer to establish controlled data exchanges, including the reference data needed to link test results to engines, builds and components.
- Monitor data freshness, pipeline failures, processing performance and cloud consumption. Tune storage, retention and compute against agreed engineering and cost requirements.
- Use source control, peer review, automated checks and controlled deployment. Maintain separate development and production configurations and protect credentials.
- Document pipelines, dependencies and recovery procedures. Train a nominated deputy and contribute to an agreed support and incident response model.
What you need
- Practical experience building and supporting production data pipelines on AWS
- Strong Python and SQL skills
- Understanding of incremental processing, idempotency, schema changes and data quality controls
- Experience with Git, code review, testing and repeatable deployments
- Ability to work with infrastructure as code and CI/CD practices
- Understanding of cloud access controls, service identities, encryption and secure connectivity
- Relevant qualification or equivalent practical experience
- Automotive, motorsport, aerospace, manufacturing or another test-intensive engineering environment (preferred)
Key skills
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Perks
- Bonus scheme
- Private healthcare
- 401(k) plan
- Life insurance
- 32 days annual leave
- Financial advisor access
- Employee Assistance Programs
- Subsidized on-site dining
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