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# Data Engineer - Resource Demand

- **Company:** General Motors
- **Location:** Warren, MI, United States
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Microsoft Excel, Big Data, Spreadsheets, Cloud Database, Code Reuse, Data Sharing, Data Structures, Decision Support Systems, Distributed Computing Environment, Distributed Systems, Python (Programming Language), Metadata, Power BI, Sql Optimization, Data Management, Tools for Reporting, Data Delivery, Data Pipelines, Databricks
- **Published:** August 11, 2026
- **Apply:** https://us.experteer.com/career/view-jobs/data-engineer-resource-demand-warren-mi-usa-58894505

## About the Role

via quality checks, metadata, lineage, documentation, standards, monitoring, and clear ownership practices * Automate manual processes, optimize data delivery, and support interactive reporting or applications reducing spreadsheet dependency * Develop datasets and delivery mechanisms for scenario modeling, capacity vs demand analysis, utilization reporting, forecast support, and leadership planning insights * Write reusable code and data structures, and resolve data-related issues to improve quality, scalability, and long-term supportability Tasks * Bachelor's degree in a quantitative field * 2 years of experience as a data engineer, analytics engineer, or software/data developer * Proficiency in Python or similar, advanced SQL, Databricks or distributed processing tools, and reporting tools such as Power BI and Excel * Experience building reliable data structures for large datasets and reporting tools * Working knowledge of data quality, metadata, lineage, observability, distributed aaaa
aaaau_ and cloud data environments * Ability to automate manual work, stay organized in a dynamic environment, and communicate effectively with partners Key requirements *

## Description

Experteer Overview In this role you will design and maintain production-ready data pipelines, curated datasets, and reusable data products to support planning decisions at GM. You will collaborate with cross-functional teams to translate needs into reliable data workflows on Databricks, enabling faster reporting and reducing spreadsheet reliance. You will implement data quality, metadata, lineage, and observability to build trust in shared data products. You will automate manual processes and support scenario modeling, capacity vs. demand analysis, and leadership planning insights. This position directly impacts engineering planning and strategic decision-making at scale. Compensation / Benefits * Build and maintain scalable data pipelines, curated Databricks data models, and reusable datasets for reporting, analytics, and decision support * Partner with analysts, technical teams, and business stakeholders to translate needs into reliable data products and workflows * Improve data trust via quality checks, metadata, lineage, documentation, standards, monitoring, and clear ownership practices * Automate manual processes, optimize data delivery, and support interactive reporting or applications reducing spreadsheet dependency * Develop datasets and delivery mechanisms for scenario modeling, capacity vs demand analysis, utilization reporting, forecast support, and leadership planning insights * Write reusable code and data structures, and resolve data-related issues to improve quality, scalability, and long-term supportability Tasks * Bachelor's degree in a quantitative field * 2 years of experience as a data engineer, analytics engineer, or software/data developer * Proficiency in Python or similar, advanced SQL, Databricks or distributed processing tools, and reporting tools such as Power BI and Excel * Experience building reliable data structures for large datasets and reporting tools * Working knowledge of data quality, metadata, lineage, observability, distributed computing, and cloud data environments * Ability to automate manual work, stay organized in a dynamic environment, and communicate effectively with partners Key requirements *


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