Senior Data Engineer
$138,700–$175,450 year
Hybrid · Austin, Texas, United States or Warren, Michigan, United States
Job Summary
Senior Data Engineer role leading design, build, and productionize of reliable, scalable data pipelines and data products in Azure Databricks to support AI, analytics, and operational use cases. Hybrid work arrangement with in-person cadence at GM Warren Global Technical Center or Austin Technical Center; collaborate with data scientists, analysts, software engineers, and business teams; mentor junior engineers; contribute to technical direction and engineering best practices; ensure data accessibility, trustworthiness, and governance for analytics and AI-enabled use cases. Role emphasizes building data infrastructure, transforming raw data into trusted datasets, supporting model development workflows, and enabling feature-ready data for experimentation and deployment.
Required Qualifications
- Bachelor’s degree in Computer Science, Software Engineering, or related field, or equivalent experience
- 5+ years of relevant full-time experience
- Strong experience in data engineering, including pipeline development, data modeling, data integration, and production support for enterprise data platforms
- Data engineering experience, including Python or Scala, SQL, and relational/non-relational data storage (ETL frameworks, big data processing, NoSQL)
- Experience with cloud platforms – Azure preferred; AWS or GCP also considered
- Proficiency with SQL, key-value datastores, and document stores
- Design, build, and optimize scalable batch and streaming data pipelines using Databricks (Apache Spark, Delta Lake) to support Medallion Architecture
- Experience with modern cloud data platforms, distributed processing, and production-grade data pipelines
- Demonstrated ability to work independently, manage broad technical challenges, and deliver solutions with limited guidance
- Experience collaborating across engineering, analytics, and business teams to deliver data solutions that support measurable outcomes
- Understanding of statistics, machine learning, experimentation, and data mining concepts used to drive informed decisions
- Ability to prepare and explore data, support model development workflows, and help validate analytical outputs in partnership with data scientists
- Ability to translate analytical needs into scalable data solutions and help move data science work from exploration into repeatable, governed delivery
- Strong communication skills to connect technical work with business value and convert complex findings into clear recommendations
- Master’s degree in Computer Science, Software Engineering, or related field (preferred)
- Experience supporting AI or machine learning use cases through strong data foundations, feature engineering support, experimentation enablement, or model-ready data preparation (preferred)
- Experience working in environments where data engineering and data science operate closely together to deliver business value at scale (preferred)
- Demonstrated mentoring, technical leadership, and process improvement impact consistent with a Level 7 senior individual contributor role (preferred)
- This job may be eligible for relocation benefits (preferred)
- Compensation: The expected base compensation for this role is: $138,700 - $175,450.
- Bonus Potential: An incentive pay program offers payouts based on company performance, job level, and individual performance.
- Benefits: GM offers a variety of health and wellbeing benefit programs.
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