Data Engineering Manager - Lakehouse & AI Platform

General Motors; Warren (MI); Hybrid; USD 180,000 - 230,000; Full time

Job summary

General Motors is seeking a Data Engineering Manager to lead a team building Customer data platforms for OnStar, Connected Services, Marketing, and AI initiatives. You will drive scalable, cloud-native Lakehouse architectures across Azure, AWS, and GCP, while guiding data products from concept to production.

You’ll mentor engineers, shape the technical roadmap, and collaborate with cross-functional teams to enable GenAI and real-time analytics at scale, powering millions of connected customer

Qualifications

• Bachelor’s degree in computer science, Engineering, Information Systems, or related field.
• 7+ years of experience in Data Engineering, Software Engineering, or production grade Distributed Data Platforms.
• 3+ years of proven experience leading and managing data engineering or software engineering teams.
• Deep expertise with Databricks, Apache Spark, Delta Lake, Unity Catalog, Python, SQL, and modern Lakehouse architectures.
• Experience designing cloud-native solutions across Azure, AWS, or GCP.
• Strong understanding of data modeling, data governance, observability, security, and engineering best practices.
• Experience with or exposure to AI-first engineering concepts, including Generative AI, Agentic AI, Retrieval-Augmented Generation (RAG), vector search, and LLM-powered applications.

Responsibilities

• Lead, mentor, and grow a high-performing team of Data Engineers, including performance management, career development, hiring and onboarding.
• Define and execute the technical roadmap for Customer, Marketing, and OnStar Digital data products, using cloud-agnostic architecture enabling interoperability across Azure, AWS, GCP.
• Architect, design and build scalable batch, streaming, API, and event-driven data pipelines using Databricks, Spark, Delta Lake, and Unity Catalog.
• Own end-to-end delivery of data engineering initiatives from product requirements to operational support post deploy.
• Drive modernization from legacy platforms to cloud-native, multi-cloud Lakehouse architectures.
• Enable AI and Machine Learning by building trusted, reusable, and governed data products supporting predictive analytics, GenAI, and LLM apps.
• Collaborate with architecture and platform teams to align reference architectures, standards, and reusable components.
• Champion engineering excellence through CI/CD, Infrastructure as Code, Data Observability, automated testing, metadata management, and data quality.
• Optimize platform performance, scalability, reliability, and cloud cost efficiency.
• Collaborate with Business, Product, Marketing, Analytics, Security, and Architecture teams to deliver business outcomes and technical innovation.
• Foster a culture of innovation, continuous learning, experimentation, and engineering excellence.

Skills

Databricks

Apache Spark

Delta Lake

Unity Catalog

Python

SQL

Cloud platforms

Leadership

Stakeholder management

Education

Bachelor’s degree in computer science, Engineering, Information Systems, or related field

Tools

Azure

AWS

GCP

Kafka

Azure Event Hubs

Job description

General Motors is seeking a Data Engineering Manager to lead a team building Customer data platforms for OnStar, Connected Services, Marketing, and AI initiatives. You will drive scalable, cloud-native Lakehouse architectures across Azure, AWS, and GCP, while guiding data products from concept to production.

You’ll mentor engineers, shape the technical roadmap, and collaborate with cross-functional teams to enable GenAI and real-time analytics at scale, powering millions of connected customer