Data Engineering Manager

This role owns the technical direction, delivery, reliability, and continuous improvement of a cloud-based engineering data platform. The platform brings together large volumes of vehicle test and engineering data from multiple sources and makes it governed, discoverable, and ready for analytics.

The successful candidate will combine people leadership, technical judgment, product-minded execution, stakeholder management, and operational accountability. This leader will build a high-performing team and establish scalable data engineering practices across vehicle engineering and related organizations.

What You’ll Do

• Lead, develop, and inspire a team of data engineers and technical leads.

• Set the roadmap, priorities, and execution strategy for engineering data products.

• Translate engineering, analytics, and machine learning needs into scalable delivery plans.

• Guide data ingestion, processing, transformation, cataloging, quality, and publication.

• Establish reusable patterns for raw, normalized, and analytics-ready data layers.

• Drive data quality, observability, lineage, governance, security, and operational readiness.

• Partner with vehicle engineering, calibration, diagnostics, performance engineering, data science, platform engineering, and product teams.

• Prioritize competing requests and manage scope, dependencies, risks, and delivery commitments.

• Support multiple data formats and high-volume engineering, telemetry, time-series, and test data.

• Promote reusable architecture and reduce duplicate pipelines across engineering organizations.

• Establish production support practices, incident response, runbooks, service health metrics, and continuous improvement.

• Champion automation, infrastructure as code, continuous integration and delivery, testing, and secure cloud deployment.

• Communicate technical strategy, delivery status, tradeoffs, and risks to senior leadership.

• Build strong relationships with internal customers and ensure data products are discoverable and usable.

• Develop talent through coaching, feedback, career planning, and meaningful technical opportunities.

Lead change management as the platform expands to new data sources, users, and use cases. *, This role is categorized as hybrid. This means the selected candidate is expected to report to a specific location at least 3 times a week {or other frequency dictated by their manager}.

• Bachelors degree in Computer Science, Engineering, Information Technology, Data Science, or a related field, or equivalent experience.

• Ten or more years of experience in software engineering, data engineering, platform engineering, or a related technical discipline.

• Five or more years of experience leading engineering teams, including people management responsibilities.

• Experience designing and operating enterprise-scale data platforms or distributed data pipelines.

• Experience with cloud data platforms, data lakes, lakehouse architecture, or large-scale analytics systems.

• Strong understanding of data modeling, data quality, metadata, lineage, governance, and access management.

• Experience delivering production systems with monitoring, alerting, incident response, and service-level expectations.

• Experience leading technical roadmaps across multiple teams and organizational boundaries.

• Ability to communicate complex technical concepts clearly to technical and nontechnical audiences.

• Demonstrated ability to manage priorities, resolve ambiguity, and deliver measurable outcomes.

• Strong written, verbal, analytical, and problem-solving skills.

Willingness to travel occasionally based on business needs. *

What Can Give You a Competitive Advantage (Preferred Qualifications )

• Masters degree in Computer Science, Engineering, Data Science, or a related field.

• Experience supporting automotive, mobility, manufacturing, embedded systems, vehicle testing, or engineering analytics.

• Experience building data products used by engineering, calibration, diagnostics, simulation, or machine learning teams.

• Experience scaling ingestion and processing for large files, high-volume telemetry, or time-series data.

• Experience with data cataloging, business metadata, data contracts, data mesh, or domain-oriented data products.

• Experience managing vendor, supplier, or cross-functional delivery relationships.

• Experience establishing platform cost-management and capacity-planning practices.

• Experience with data observability and quality tools.

• Experience leading cloud modernization or migration from legacy data platforms.

• Experience working in an Agile or product-oriented engineering environment.

• Experience with Six Sigma, Lean, DevOps, or similar continuous-improvement methods.

We believe we all must make a choice every day - individually and collectively - to drive meaningful change through our words, our deeds and our culture. Every day, we want every employee to feel they belong to one General Motors team., General Motors is committed to being a workplace that is not only free of unlawful discrimination, but one that genuinely fosters inclusion and belonging. We strongly believe that providing an inclusive workplace creates an environment in which our employees can thrive and develop better products for our customers.