Data Engineer - Supplier Quality Data Analytics

General Motors • Warren, MI

7d • Hybrid

About The Position

The Supplier Quality Data Analytics Group is seeking a highly motivated and technically skilled Data Engineer to support data-driven decision-making across the Global Supplier Quality organization. In this role, you will design, develop, and maintain scalable data pipelines and analytics solutions that enhance supplier quality performance, reporting, and operational efficiency. You will work in a modern data environment, collaborating with cross-functional stakeholders to deliver high-quality, reliable data that powers actionable insights and continuous improvement across GM’s supply base.

Requirements

• Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related technical field.
• Minimum 3 years of experience in data engineering or analytics roles.
• Proficiency in SQL and Python for data manipulation, automation, and ETL development.
• Experience with data visualization tools such as Power BI.
• Familiarity with cloud platforms (e.g., Azure, AWS) and big-data technologies (e.g., Spark, Databricks).
• Strong understanding of data modeling, data warehousing, and pipeline architecture.
• Excellent analytical, problem-solving, and communication skills.
• Ability to work independently and collaboratively in a fast-paced, cross-functional environment.

Nice To Haves

• Experience working with supplier quality data or manufacturing analytics.
• Hands-on experience with Microsoft Fabric and its components (Lakehouse, Dataflows, Notebooks).
• Knowledge of Slack automation and SharePoint integration.
• Certifications in Databricks, Dataloop, or Microsoft Fabric.
• Familiarity with GM systems such as SQMS, MARS, and SPCR workflows.
• Previous experience supporting dashboard development and data governance in a corporate or manufacturing setting.

Responsibilities

• Develop Data Pipelines: Design, build, and optimize ETL pipelines for ingesting, transforming, and storing supplier quality data from multiple sources, ensuring high performance and scalability for large datasets.
• Model and Store Data: Implement relational and dimensional data models to support analytics and reporting, using tools such as SQL, Databricks, Microsoft Fabric, and Dataloop.
• Support Analytics and Reporting: Prepare clean, structured datasets for dashboards and reports in Power BI. Collaborate with data analysts and quality engineers to ensure data accuracy, usability, and consistency.
• Automate and Integrate Systems: Develop and maintain automation workflows using Python. Integrate data solutions with collaboration tools such as Slack and SharePoint for streamlined processes.
• Maintain Data Governance and Security: Ensure compliance with corporate data standards. Monitor data integrity and troubleshoot issues across pipelines, models, and dashboards.

Benefits

• From day one, we're looking out for your well-being–at work and at home–so you can focus on realizing your ambitions. Learn how GM supports a rewarding career that rewards you personally by visiting Total Rewards resources.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees