Data Engineering Manager - AI/ML & Multi-Cloud Lakehouse

General Motors LLC; Texas; Hybrid; USD 150,000 - 190,000; Full time

Benefits offered by this job

Hybrid work

Relocation benefits

Job summary

General Motors seeks a Data Engineering Manager to lead a team delivering customer data platforms powering OnStar, Connected Services, Marketing, and AI initiatives. You will architect scalable, cloud-native data products across a multi-cloud Lakehouse using Databricks, Spark, Delta Lake, and Unity Catalog.

You will mentor engineers, drive modernization, and enable AI-ready data solutions with strong governance and observability, collaborating across GM teams and platforms.

Qualifications

• 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.
• Strong experience building large-scale distributed batch and streaming data pipelines.
• Excellent leadership, communication, and stakeholder management skills, with the ability to translate business needs into technical solutions.

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, portable architecture that enable interoperability across Azure, GCP, AWS, and other platforms while supporting GM’s long-term multi-cloud strategy.
• Architect, Design and build scalable batch, streaming, API, and event-driven data pipelines using Databricks, Apache 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 applications.
• 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

Lakehouse architectures

Cloud platforms

Distributed data processing

Real-time streaming

AI/ML / GenAI

Leadership / people management

CI/CD

Education

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

Job description

General Motors seeks a Data Engineering Manager to lead a team delivering customer data platforms powering OnStar, Connected Services, Marketing, and AI initiatives. You will architect scalable, cloud-native data products across a multi-cloud Lakehouse using Databricks, Spark, Delta Lake, and Unity Catalog.

You will mentor engineers, drive modernization, and enable AI-ready data solutions with strong governance and observability, collaborating across GM teams and platforms.