The Role General Motors is seeking a data engineering manager to lead a team responsible for building and operating scalable data products that support engineering vehicle analysis, testing, diagnostics, machine learning, and downstream applications. 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 Youll 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. Your Skills & Abilities (Required Qualifications)  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. GM does not provide immigration-related sponsorship for this role. Do not apply for this role if you will need GM immigration sponsorship now or in the future. This includes direct company sponsorship, entry of GM as the immigration employer of record on a government form, and any work authorization requiring a written submission or other immigration support from the company (e.g., H1-B, OPT, STEM OPT, CPT, TN, J-1, etc).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}.The selected candidate will be required to travel on a regular basis (25-50%) for this role.Relocation benefits are available for candidates who qualify under company policy.