Vehicle Propulsion Data Engineer – GCP & Tekton

About the role

The Vehicle Propulsion Systems Engineering team is looking for a data engineer to design, build, and operate cloud‑native analytics pipelines for powertrain datasets. The role combines data engineering, DevSecOps, and automotive domain knowledge to deliver trusted insights quickly.

Key responsibilities

• Design and maintain GCP‑native data pipelines using Cloud Storage, Cloud Functions, Pub/Sub, and BigQuery.
• Develop and operate Tekton CI/CD pipelines for analytics code, data workflows, and infrastructure changes.
• Implement event‑driven processing patterns and manage bucket strategies, IAM, lifecycle policies, and cost‑aware tiering.
• Apply data governance practices including quality checks, metadata standards, lineage, and documentation.
• Validate models and pipelines for data integrity, reliability, and production readiness.
• Build dashboards and reports that highlight trends, anomalies, and operational insights for engineering teams.
• Collaborate with calibration, controls, test, IT, and cybersecurity stakeholders to define requirements.
• Integrate security scanning, secret management, and release controls into CI/CD pipelines.
• Monitor production services with Cloud Logging, Monitoring, and alerting, and support incident response.

Required profile

• Bachelor’s degree in Computer Science, Data Science, Engineering, Mathematics, Statistics or a related field.
• 1‑5+ years of experience in data engineering, analytics engineering, data analysis or data science.
• Hands‑on experience with cloud‑based analytics platforms; GCP experience strongly preferred.
• Automotive or powertrain data experience is a strong advantage.

Required skills

• Google Cloud Platform – Cloud Storage, Cloud Functions, Pub/Sub, BigQuery.
• Tekton pipeline authoring and management.
• Python for data transformation and automation.
• SQL for extraction, transformation and analytical querying.
• ETL/ELT, data modeling and data warehousing concepts.
• BI tools such as Tableau, Power BI or Qlik.
• Git version control and collaborative branching/review workflows.
• Cloud Logging, Monitoring, alerting, and incident response.
• Security scanning, secret management and DevSecOps practices.