Jobs / United States / General Motors Company
Senior Data Engineering, Vehicle Data Operations
General Motors Company · 🇺🇸 2 Locations
Sponsorship verdict
Sponsorship possible
One solid signal, not two — worth applying, and worth asking about sponsorship early.
- Employer is on a government sponsor recordThe US Department of Labor certified 606 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 267 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
- The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
- No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
- What General Motors Company paid sponsored hires in similar roles2 certified filings for “Vice President, Global Vehicle Hardware Engineering” (Chief Executives) in MI: $310k–$560k, median $435k. Most were filed at wage level II (50%) — 2 lottery entries, ≈31% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).
- Confirmed live todayWhen a source last listed this job as open.
US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).
A verdict summarises public evidence; it is not legal advice and never a guarantee — the employer and the immigration authority decide. Sign in to factor in where you can already work.
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Sponsor Radar — General Motors Company
The US Department of Labor certified 606 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 267 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
Past sponsorship or register membership never guarantees sponsorship for this vacancy or for you. Full Sponsor Radar for General Motors Company →
About the role
Job Description Vacancy 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-en