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# Data Engineering Manager

- **Company:** General Motors
- **Location:** Warren, MI, United States
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Unity 3d, Artificial Intelligence, Amazon Web Services, Data Analysis, Automation of Tests, Microsoft Azure, Cloud Computing, Continuous Integration, Customer Data Management, Information Engineering, Distributed Data Store, Python (Programming Language), Cloud Services, Standard Sql, Search Technologies, Software Engineering, Data Streaming, Large Language Models, Apache Spark, Multi-Cloud, Data Lakes, Data Management, Cloud Optimization, Legacy Systems, Databricks
- **Published:** August 11, 2026
- **Apply:** https://us.experteer.com/career/view-jobs/data-engineering-manager-warren-mi-usa-58894311

## About the Role

platforms. to post-deploy support * Drive modernization to cloud-native, multi-cloud Lakehouse architectures * Enable AI/ML by building governed, reusable data products for predictive analytics and GenAI * Collaborate with architecture and platform teams to align standards and reusable components * Promote engineering excellence through CI/CD, IaC, observability, data quality, and automated testing * Optimize performance, scalability, reliability, and cloud cost efficiency * Collaborate with Business, Product, Marketing, Analytics, Security, and Architecture teams to achieve business outcomes and innovation * Foster a culture of innovation, continuous learning, and engineering excellence Tasks * 7+ years in Data Engineering, Software Engineering, or distributed data platforms * 3+ years leading data or software engineering teams * Deep expertise with Databricks, Apache Spark, Delta Lake, Unity Catalog, Python, SQL * Experience designing cloud-native solutions across Azure, AWS, or GCP *
Strong data modeling, governance, observability, security, and engineering best practices * Experience with AI-first concepts including GenAI, RAG, vector search, and LLM apps * Experience building large-scale distributed batch and streaming data pipelines * Excellent leadership, communication, and stakeholder management Key requirements * hybrid work model * relocation benefits * career development * total rewards resources * inclusive culture * opportunities to drive innovation

## Description

Experteer Overview As Data Engineering Manager you will lead a team building scalable, cloud-native data products for GM's customer data platforms. You'll steer multi-cloud Lakehouse initiatives powering OnStar, Marketing, and AI-driven analytics, delivering trusted data assets and scalable pipelines. You'll influence strategy, mentor engineers, and drive modernization from legacy systems to AI-ready data platforms. This role combines deep technical leadership with people management to enable cross-functional collaboration and impactful business outcomes. Compensation / Benefits * Lead and grow a high-performing data engineering team, including performance management and onboarding * Define and execute the technical roadmap for Customer, Marketing, and OnStar data products with multi-cloud interoperability * Architect and build scalable batch and streaming pipelines using Databricks, Spark, Delta Lake, and Unity Catalog * Own end-to-end delivery of data engineering initiatives from requirements to post-deploy support * Drive modernization to cloud-native, multi-cloud Lakehouse architectures * Enable AI/ML by building governed, reusable data products for predictive analytics and GenAI * Collaborate with architecture and platform teams to align standards and reusable components * Promote engineering excellence through CI/CD, IaC, observability, data quality, and automated testing * Optimize performance, scalability, reliability, and cloud cost efficiency * Collaborate with Business, Product, Marketing, Analytics, Security, and Architecture teams to achieve business outcomes and innovation * Foster a culture of innovation, continuous learning, and engineering excellence Tasks * 7+ years in Data Engineering, Software Engineering, or distributed data platforms * 3+ years leading data or software engineering teams * Deep expertise with Databricks, Apache Spark, Delta Lake, Unity Catalog, Python, SQL * Experience designing cloud-native solutions across Azure, AWS, or GCP * Strong data modeling, governance, observability, security, and engineering best practices * Experience with AI-first concepts including GenAI, RAG, vector search, and LLM apps * Experience building large-scale distributed batch and streaming data pipelines * Excellent leadership, communication, and stakeholder management Key requirements * hybrid work model * relocation benefits * career development * total rewards resources * inclusive culture * opportunities to drive innovation


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