Staff Data Engineer

General Motors

Staff Data Engineer building governed data products and AI-ready platforms for General Motors. Leading Azure Databricks pipelines, architecture, experimentation, and production AI enablement.

Posted 9/5/2026full-timeWarren • Missouri, Texas • 🇺🇸 United StatesLead💰 $160,200 - $211,950 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and building scalable data pipelines and products using Azure Databricks, Apache Spark, and Delta Lake. Proficient in data modeling, integration, and supporting AI use cases through feature-ready datasets and experimentation workflows.

Highest-signal resume keywords

Azure DatabricksApache SparkDelta LakeData Pipeline DevelopmentMLOps

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data EngineeringData ModelingData IntegrationSQL Performance TuningPythonScalaData Quality FrameworksObservabilityJob SchedulingCloud Platforms

Soft Skills

Strong Communication SkillsCross-Functional CollaborationTechnical LeadershipMentoringProblem Solving

Tools & Technologies

CI/CDDataOpsMachine LearningEvent-Driven ArchitecturesEnterprise Data Platforms

Industry Keywords

ManufacturingAutomotiveIndustrial IoTData GovernancePrivacy Controls

Tech Stack

Tools & technologies

ApacheAWSAzureCloudGoogle Cloud PlatformIoTPythonScalaSparkSQL

About the role

Key responsibilities & impact

Design, build, and productionize reliable, scalable, and secure data pipelines and data products in Azure Databricks
Transform raw data from heterogeneous source systems into trusted, structured, and governed datasets
Define and champion architecture, design patterns, Medallion Architecture, Delta Lake standards, data quality, and observability practices
Drive strategic improvements to data processes, delivery patterns, and technical solutions
Solve complex and non-standard data engineering problems
Partner with data scientists, analysts, software engineers, product stakeholders, and business leaders
Enable AI and data science through feature-ready data, experimentation workflows, and scalable model development, deployment, monitoring, and improvement patterns
Provide technical leadership for large multi-sprint and multi-team initiatives
Influence engineering decisions, technology choices, and long-term roadmaps
Mentor and coach engineers and data scientists through technical guidance, reviews, and knowledge sharing
Evolve DevOps, DataOps, and MLOps practices, including CI/CD, testing, observability, governance, and reliability
Communicate technical concepts, trade-offs, and recommendations to technical and non-technical audiences
Establish governed, curated, contract-backed data products and semantic models for analytics and AI applications
Contribute to multi-agent systems, agent orchestration, supervisor-agent patterns, and reusable AI services
Help establish GM’s foundation for trusted, scalable, reusable data and AI intelligence

Requirements

What you’ll need

Bachelor’s degree in Computer Science, Software Engineering, Data Engineering, or related field, or equivalent experience
8+ years of relevant full-time experience in data engineering or closely related roles, or equivalent depth of knowledge
Hands-on experience with end-to-end data pipeline development, including ingestion, transformation, orchestration, and monitoring
Experience with data modeling, data integration, and production support for enterprise data platforms
Experience building and operating reliable, scalable data products in production
Extensive experience with Databricks, Apache Spark, Delta Lake, batch and streaming pipelines, and modern cloud data patterns
Experience supporting AI or machine-learning use cases through data preparation, feature-ready datasets, experimentation workflows, and model-development enablement
Proficiency in Python or Scala
Proficiency in SQL, including performance tuning and large-scale datasets
Experience with relational and non-relational data storage technologies
Deep experience with cloud platforms; Azure strongly preferred, AWS or GCP also considered
Experience with data quality frameworks, observability, orchestration, job scheduling, performance optimization, and cost management
Ability to work independently and lead through influence on broad, ambiguous technical challenges
Experience driving cross-functional collaboration across engineering, analytics, product, and business teams
Understanding of statistics, machine learning, experimentation, and data mining concepts
Ability to prepare and explore data at scale, support model development workflows, and validate analytical outputs and production model behavior
Ability to translate complex analytical and AI needs into scalable, maintainable data solutions
Strong communication and storytelling skills
Advanced degree in a related field preferred
Experience as a principal- or staff-level engineer in large-scale cloud-based data environments preferred
Experience leading or technically directing engineers or data scientists preferred
Background in manufacturing, automotive, industrial IoT, or similar domains preferred
Experience with MLOps, data governance, privacy, security controls, event-driven and streaming architectures, and enterprise data platforms preferred
GM does not provide immigration-related sponsorship for this role; applicants must not require GM immigration sponsorship now or in the future

Benefits

Comp & perks

Bonus potential through an incentive pay program based on company, job-level, and individual performance
Potential relocation benefits
Company vehicle evaluation program, including assignment of a General Motors vehicle, subject to eligibility and program requirements
Medical, dental, and vision benefits
Health Savings Account
Flexible Spending Accounts
Retirement savings plan
Sickness and accident benefits
Life insurance
Paid vacation and holidays
Tuition assistance programs
Employee assistance program
GM vehicle discounts