Senior Data Engineering, Vehicle Data Operations

Vacancy StatusThis posting is for an existing vacancy within the organization and is open to new applications.
Job DescriptionVacancy Status: This posting is for an existing vacancy within the organization and is open to new applications.
AI Disclosure: As part of the application process, Artificial Intelligence will be used in the hiring process for this role
Work Arrangement: This role is categorized as hybrid. This means the successful candidate is expected to report to the office three days per week, at minimum.
The role: The Senior Data Engineering candidate will build, operate, and improve software and data solutions that make vehicle data operations more reliable, observable, and scalable. This position involves continuously monitoring data product quality alongside vehicle software performance and its behaviour. This role partners with vehicle data engineering, software application teams, program management, systems engineering, and quality engineering to turn operational needs into reliable pipelines, monitoring, dashboards, alerts, and support processes. The successful engineering candidate is a hands‑on technical professional who can work across the full solution lifecycle: understand the problem, define requirements, map data and system relationships, build and test the solution, deploy it, monitor it in production, document it, and improve its reliability, performance, scalability, and cost.
What You'll Do (Responsibilities)
Define technical requirements, metrics, acceptance criteria, monitoring needs, and operational response paths.
Design, execute, and refine scalable data pipelines, automated workflows, monitoring dashboards, system alerts, analytics queries, testing frameworks, and governance standards.
Monitor vehicle data campaigns, package propagation, and eligible vehicle populations across operational systems.
Lead and support data investigations to ensure accurate data capture and high data quality/integrity.
Create logging, metrics, dashboards, and alerts that enhance operational observability and overall fleet software behaviour.
Use data from multiple systems to understand vehicle lifecycle states, campaign status, package delivery, and operational outcomes.
Define requirements and acceptance criteria for external and dependent teams;
document data flows, data lineage, operating procedures, and support guidance.
Communicate technical findings, risks, limitations, and recommendations to both technical and non-technical audiences.
Contribute reusable patterns, engineering best practices, design guidance, and mentoring within the team and broader organization.
Work effectively in a fast‑paced, collaborative environment and contribute positively to team culture.
Expected business outcomes
Deliver committed data engineering and observability capabilities with clear acceptance criteria, validation evidence, and production-support plans.
Improve visibility into vehicle data campaigns, package propagation, vehicle populations, and operational system health.
Support data related production investigations and resolutions.
Improve the reliability, performance, scalability, usability, and cost of existing data operations and observability solutions.
Reduce manual effort, speed up issue investigation, improve launch readiness, and support earlier risk mitigation.
Strengthen engineering governance through documented definitions, data quality checks, lineage, testing, and repeatable operating practices.
Your Skills & Abilities (Required Qualifications)
5+ years of experience building, deploying, or supporting software, data engineering, platform, or observability solutions.
Bachelor’s degree in Engineering, Computer Science, Data Science, or a related field;
equivalent practical experience may be considered.
Hands‑on experience with building and optimizing end‑to‑end data pipelines in Databricks, including deployment of DBX applications and workflows.
Strong SQL skills and hands‑on experience working with large and complex datasets, data pipelines, workflow orchestration, or comparable data platforms.
Strong scripting and programming skills for automation, data processing, integration, validation, and production workflows (Python, Bash/Shell, etc.).
Familiarity with modern deployment practices such as Git‑based workflows, CI/CD, infrastructure‑as‑code, or Databricks Asset Bundles.
Ability to drive software engineering best practices across development, testing, deployment, documentation, observability, and production support.
Ability to work with vehicle‑level and population‑level data to support operational decisions.
Experience building operational dashboards (Grafana, Datadog, DBX), alerting, logging, monitoring, or decision‑support solutions.
Demonstrated ability to lead technical work across teams and collaborate effectively with partners, customers, and dependent teams.
Experience participating in design discussions, code reviews, technical planning, knowledge sharing, or mentoring.
Positive contributor who takes ownership, communicates clearly, supports team development, and helps build a collaborative and inclusive team environment.
What Can Give You a Competitive Advantage (Preferred Qualifications)
Experience with Azure data services, Data Factory, Datadog, cloud data platforms, or workflow orchestration.
Experience with vehicle, telematics, diagnostic, warranty, software‑version, campaign, package, product‑launch, or fleet data.
Experience with CI/CD and DevOps tools or platforms such as GitHub Actions, Jenkins, Buildkite, Azure DevOps, or comparable technologies.
Experience with Docker or other container technologies, artifact management, automated release promotion, cloud deployment, or infrastructure automation.
Familiarity with Fluent Bit and associated applications, plug‑ins, and operational tools.
Experience designing service‑level indicators or operational metrics for connectivity, deployment, coverage, delivery, reporting, and campaign health.
Familiarity with data modeling, data lineage, reusable engineering patterns, scalable solution design, and governed catalogs.
Familiarity with AI/ML methods that can improve detection quality while controlling false positives and operational burden.
CompensationThe salary range for this role is $115,000 to $164,600. The actual base salary a successful candidate will be offered within this range will vary based on factors relevant to the position.
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.
Benefits Overview
Paid time off including vacation days, holidays, and supplemental benefits for pregnancy, parental and adoption leave;
Healthcare, dental, and vision benefits;
Life insuranceplans to cover you and your family;
Company and matching contributions to a Defined Contribution Pension plan to help you save for retirement;
GM Vehicle Purchase Plan for you and your family.
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We encourage interested candidates to review the key responsibilities and qualifications for each role and apply for any positions that match their skills and capabilities. Applicants in the recruitment process may be required, where applicable, to successfully complete a role‑related assessment(s) and/or a pre‑employment screening prior to beginning employment. To learn more, visit
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