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Senior Software Engineer - Vehicle Engineering and Quality

LinkedIn General Motors Austin, TX
Not Applicable Posted March 27, 2026 2 variants Job link
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Requirements
  • 6+ years of experience delivering enterprise or full stack software solutions using Java / JEE, Python, and preferably Angular.
  • 3+ years of experience working with complex SQL queries, functions, and stored procedures, including performance tuning and optimization against large datasets.
  • Experience building or supporting data pipelines, ETL/ELT processes, or datacentric applications on distributed or cloud platforms (e.g., Databricks, Spark, or similar).
  • 3+ years of experience with Kubernetes/Docker, Quarkus, and cloud platforms such as Azure, AWS, or GCP.
  • Experience working in Agile/SCRUM development methodologies, including backlog refinement, sprint planning, and incremental delivery.
  • Handson experience with modern DevOps practices such as Git/GitHub, code reviews, automated builds, automated testing, and CI/CD pipelines (e.g., GitHub Actions).
  • Willingness and demonstrated ability to learn and apply AI concepts, including working with data and APIs that support AI/ML and LLM based solutions.
  • Strong problem solving skills with the ability to break down complex technical and data challenges into clear, actionable steps and deliver high quality solutions.
  • Excellent written and verbal communication skills with the ability to collaborate with both technical and nontechnical stakeholders.
  • Demonstrated ownership mindset, accountability for quality, and focus on delivering measurable value to internal customers.
Preferred Skills
  • Master’s Degree in Computer Science, Engineering, Information Systems, or a related field.
  • 10+ years of experience delivering enterprise grade or global, scalable software applications, including data intensive or analytics focused solutions.
  • Deep hands on experience with Databricks (Delta tables, notebooks, jobs, workflows) and/or Spark for data engineering, analytics, or AI workloads.
  • Proven experience migrating applications and complex data workloads to Azure or other cloud platforms, including use of managed data, messaging, and API services.
  • Experience working with or supporting AI/ML initiatives (e.g., feature engineering, model integration, AI/LLM service integration, monitoring, and ML Ops concepts).
  • Knowledge of relational and dimensional data modeling, data quality practices, metadata management, and data governance in an enterprise environment.
  • Experience with observability and reliability practices (logging, metrics, tracing, dashboards, alerting, SRE concepts) for data and application services.
  • Demonstrated ability to influence technical direction, establish reusable patterns and standards, and mentor less experienced engineers.
  • Ability to manage multiple initiatives and priorities in a fast-paced environment while maintaining high engineering standards.
Education
  • (Not required) – Bachelor’s Degree in Computer Science, Software Engineering, Information Systems, Engineering, or a related field, OR equivalent experience.
  • (Not required) – Master’s Degree in Computer Science, Engineering, Information Systems, or a related field.