Data Engineer - Resource Demand

Experteer Overview In this role you will design and maintain production-ready data pipelines and reusable data products to speed planning and improve decision-making for engineering teams. You’ll work with a cross-functional team to translate needs across resource demand, portfolio, workforce, and finance into reliable data solutions. The role focuses on Databricks data models, data quality, and scalable delivery to reduce manual work and enhance reporting. You will contribute to faster forecast confidence, better operational visibility, and data-driven planning at GM. This opportunity lets you shape versatile data platforms in a globally influential mobility company. Compensation / Benefits * Build and maintain scalable data pipelines and Databricks data models to support reporting, analytics, and decision support. * Collaborate with analysts and stakeholders to translate resource demand, portfolio, workforce, and finance needs into data products and workflows. * Improve data trust via quality checks, metadata, lineage, and clear ownership practices. * Automate manual processes and enable interactive reporting that reduces spreadsheet use. * Develop datasets for scenario modeling, capacity vs. demand analysis, utilization reporting, and leadership planning insights. * Write reusable code and data structures; resolve data-related issues to improve scalability and long-term support. Tasks * Bachelor’s degree in a quantitative field. * 2 years of data engineering or related experience building production data pipelines, models, or reporting solutions. * Proficiency in Python or similar, advanced SQL, and experience with Databricks or similar distributed processing tools; familiarity with Power BI and Excel. * Experience building reliable data structures for large datasets and data-driven applications. * Working knowledge of data quality, metadata, lineage, observability, distributed computing, and cloud data environments. * Ability to automate processes, stay organized in a dynamic environment, and communicate effectively with partners. Key requirements *

_ quality checks, metadata, lineage, and clear ownership practices. * Automate manual processes and enable interactive reporting that reduces spreadsheet use. * Develop datasets for scenario modeling, capacity vs. demand analysis, utilization reporting, and leadership planning insights. * Write reusable code and data structures; resolve data-related issues to improve scalability and long-term support. Tasks * Bachelor’s degree in a quantitative field. * 2 years of data engineering or related experience building production data pipelines, models, or reporting solutions. * Proficiency in Python or similar, advanced SQL, and experience with Databricks or similar distributed processing tools; familiarity with Power BI and Excel. * Experience building reliable data structures for large datasets and data-driven applications. * Working knowledge of data quality, metadata, lineage, observability, distributed computing, and cloud data environments. * Ability to automate processes, stay organized P _ a dynamic environment, and communicate effectively with partners. Key requirements *