Data Engineer - Supplier Quality Data Analytics

Description

This role is categorized as hybrid. This means the successful candidate is expected to report to Warren, Michigan, three times per week, at minimum.

The Role

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.

What You'll Do

• 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.

• 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.

• 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.