WHY JOIN GENERAL MOTORS INSURANCE DATA ANALYTICS?

We’re building the next great business within General Motors—an insurance company designed to disrupt the traditional model by leveraging our unique position as the largest U.S. automaker. Our competitive edge lies in our ability to make principled, data-driven decisions at scale. By combining telematics, machine learning, and a deep understanding of our customers, we’re creating a seamless, intelligent insurance experience that GM vehicle owners will love.

EXPERIENCE AND EDUCATION

• 2-4 years of hands-on experience with data engineering required
• Bachelor’s Degree in related field or equivalent experience required
  What We Offer: Generous benefits package available on day one to include: 401K matching, bonding leave for new parents (12 weeks, 100% paid), tuition assistance, training, GM employee auto discount, community service pay and nine company holidays.
  Our Culture: Our team members define and shape our culture — an environment that welcomes innovative ideas, fosters integrity, and creates a sense of community and belonging. Here we do more than work — we thrive.
  Compensation: Competitive pay and bonus eligibility
  Work Life Balance: Remote work environmen

ABOUT THE ROLE

We’re expanding our decision support capabilities and seeking a data-driven professional to help scale the ingestion and processing of large, complex data sets. This role is critical to enabling smarter business decisions through advanced analytics and data science—across both batch and streaming environments—to drive growth, improve operational efficiency, and reduce costs.

KEY RESPONSIBILITIES

• Partner with cross-functional teams to identify, capture, and structure data from internal systems, external sources, and data warehouses.
• Design, build, and maintain scalable data pipelines with a focus on automation, deployment, and monitoring.
• Collaborate with business stakeholders, data scientists, analysts, and engineers to operationalize data assets that inform strategic decisions.
• Build automated testing and quality control of data pipelines and surface issues to operational teams
• Architect, build, and maintain foundational data models and reporting/consumption layers in dbt
• Support research and experimentation with modern data engineering technologies for both batch and streaming use cases
• Ensure compliance with company policies and procedures and perform other duties as assigned