Senior Data Engineer - Vehicle Quality Engineering

GM•Warren, MI

3d•Hybrid

About The Position

The Senior Data Engineer develops and operationalizes analytical solutions to identify emerging vehicle, software, and product-quality issues before they become larger customer or launch risks. The role partners with Product Quality, Warranty, Vehicle Engineering, software teams, and other subject matter experts to turn operational questions into reliable metrics, detection algorithms, dashboards, and alerting workflows. The successful candidate applies statistical and analytical judgment while building production-ready data products across the full lifecycle: understanding customer problems, validating data, developing and testing analytical approaches, deploying solutions, monitoring performance, and improving adoption and scalability. The position supports vehicle and software launches, delivers readiness insights, and improves the reliability, usability, performance, and cost efficiency of analytics products. This is a hybrid role. The successful candidate is expected to report to the Warren Global Technical Center or Austin Technical Center at least three times per week, or more frequently if business needs dictate. The position may be eligible for relocation benefits.

Requirements

Bachelor’s degree in Data Science, Statistics, Computer Science, Engineering, Mathematics, or a related field, or equivalent practical experience.
At least 7 years of data engineering/development or related experience.
Experience applying statistical analysis, machine learning, anomaly detection, forecasting, classification, or related data-science methods to real-world business or engineering problems.
Strong Python skills for data analysis, algorithm development, automation, and production-oriented data workflows.
Experience querying, transforming, validating, and analyzing large and complex datasets using SQL and modern data technologies.
Demonstrated ability to take an analytical solution from problem definition through testing, deployment, monitoring, and continuous improvement.
Experience communicating analytical results and recommendations to stakeholders with varying levels of technical expertise.
Strong data-quality mindset, including the ability to investigate discrepancies, assess assumptions, and explain limitations.
Demonstrated ownership, sound judgment, responsiveness, and ability to complete work in a cross-functional environment.

Nice To Haves

Experience with Azure data services, Data Factory, Databricks, data pipelines, workflow orchestration, or comparable cloud technologies.
Experience building operational dashboards, alerting tools, or decision-support products for engineering, quality, warranty, manufacturing, fleet, or customer-facing teams.
Experience working with vehicle, telematics, diagnostic, warranty, software-version, or product-launch data.
Experience with time-series data, event data, fleet-level analysis, VIN-level investigation, or software-quality monitoring.
Experience with modern deployment practices such as Git-based workflows, CI/CD, or Databricks Asset Bundles.
Familiarity with data modeling, data lineage, reusable analytical patterns, and scalable solution design.
Experience evaluating whether AI/ML methods can improve detection quality while controlling false positives and operational burden.
Experience mentoring peers, sharing technical best practices, or leading work across organizational boundaries.

Responsibilities

Partner with subject matter experts to define meaningful metrics, analytical objectives, thresholds, and decision criteria.
Analyze vehicle, software, warranty, diagnostic, fleet, and product-quality data to identify trends, anomalies, relationships, and emerging risks.
Design, test, and deploy anomaly-detection and pre-emptive-monitoring algorithms for customer-impacting issues.
Build end-to-end analytical pipelines that transform raw data into reliable insights, dashboards, alerts, and operational workflows.
Create customer-focused visualizations that help engineering and quality teams investigate fleet, VIN, and software-version data.
Develop alerting solutions that help internal customers respond quickly to high-priority vehicle and product issues.
Establish validation approaches using historical data, controlled testing, domain expertise, and, when appropriate, real-world observations.
Communicate findings, assumptions, limitations, and recommendations to technical and non-technical audiences.
Improve the performance, scalability, reliability, and cost efficiency of solutions through model, query, pipeline, and architecture improvements.
Reduce complexity and redundant data handling by standardizing analytical processes and adopting modern Azure-based technologies.
Support vehicle and software launches by delivering readiness insights and analytical tools.
Document analytical methods, data lineage, operating procedures, and known limitations.
Contribute reusable patterns and best practices, and mentor others in the analytics organization.
Deliver committed analytics features with clear acceptance criteria and production support plans.
Improve pre-emptive monitors, dashboards, and alerts that support data-driven decisions and earlier risk mitigation.
Work with software domains and operational teams to increase adoption and identify where analytics capabilities should expand.
Strengthen analytical governance through documented definitions, validation methods, data-quality checks, and repeatable practices.
Develop detection for emerging product-quality issues and customer-impacting patterns, including algorithms to summarize suspect charging behavior or stations.
Improve ingestion, query, and dashboard performance while reducing manual preparation and cloud-resource costs.
Integrate warranty, diagnostic, software, and operational signals to improve detection confidence and business context.

Benefits

Health and wellbeing benefit programs, including medical, dental, and vision options.
Health Savings Account and 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.
Incentive pay program with payouts based on company performance, job level, and individual performance.
Potential relocation benefits.