Data Engineer II - General Motors Insurance

JOB DESCRIPTION

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.

RESPONSIBILITIES

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.

• 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

• Proficiency in processing large-scale data sets using SQL, Python, R, or similar technologies in distributed systems.
• Experience ingesting and transforming diverse data formats (CSV, JSON, Parquet) from various sources.
• Familiarity with cloud platforms (Azure, AWS, GCP) and tools like Azure Databricks.
• Understanding of cloud computing concepts, business drivers, and emerging trends.
• Working knowledge of object storage technologies (e.g., Data Lake Storage Gen2, Amazon S3).
• Strong background in Agile/Scrum methodologies and Application Lifecycle Management.
• Proficiency with version control (Git/Subversion), artifact repositories (e.g., Artifactory), and CI/CD tools (e.g., Azure DevOps).
• Experience designing and maintaining clean, performant, scalable ETL processes.
• Awareness of IT governance, privacy compliance, and data security standards.
• Familiarity with Adobe Experience Platform, DTM/Launch, and RESTful APIs is a plus
• Has experience building in one or more BI tools (e.g., Power BI, Tableau, Thoughtspot) and using version control.
• Proficiency with DBT or other semantic modeling layers (ie: Looker/lookml).
• Strong problem-solving skills and ability to troubleshoot complex issues across teams.
• Advanced SQL expertise with the ability to derive insights from large datasets.
• Create logical and physical data models to support cloud data warehousing initiatives.
• Advanced digital data collection and computer skills.
• Excellent communication skills-verbal, written, and interpersonal.
• Knowledge of digital marketing and data technologies (DMPs, CDPs, Tag Management, SDKs, Cross-Device Tracking).
• Understanding of real-time CDPs and Adobe Customer Journey Analytics.
• Solid grasp of big data architectures, stream processing, data lakes, and lakehouse environments.
• Understanding of GDPR, data privacy, and security best practices.

• 2-4 years of hands-on experience with data engineering required
• Bachelor's Degree in related field or equivalent experience required