Jobs / United States / General Motors Company
Manufacturing Cybersecurity Data Engineer
General Motors Company · 🇺🇸 Warren, Michigan, United States of America
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 roles35 certified filings for “Manufacturing Engineer” (Industrial Engineers) in MI: $123k–$139k, median $132k. Most were filed at wage level IV (77%) — 4 lottery entries, ≈61% 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 The Role General Motors is transforming the future of mobility while operating one of the world’s most complex manufacturing environments. The Manufacturing Cybersecurity team helps protect the technology, systems, and data that keep GM plants safe, resilient, and productive. As a Manufacturing Cybersecurity Engineer, you’ll build and operate the data foundation that enables OT cyber-risk visibility across GM manufacturing. You’ll develop reliable data-ingestion and ETL solutions that consolidate vulnerability, asset, configuration, and security telemetry from plant systems, cybersecurity tools, enterprise platforms, and other sources into the Databricks Lakehouse Platform. Using Python, SQL, scripting, and data-quality practices, you’ll transform, validate, monitor, and troubleshoot pipelines, then translate complex technical data into actionable insights through Power BI or similar dashboards and reports. This is a hands-on Level 6 individual contributor role. You’ll exercise independent judgment to resolve non-routine data and cybersecurity problems, propose process improvements, and coordinate delivery across cybersecurity, manufacturing, plant, data engineering, and technology stakeholders. Your work will help plant teams prioritize remediation, reduce OT exposure, and make informed decisions without disrupting production. What You'll Do • Design, develop, operate, and maintain dependable data ingestion and ETL pipelines that consolidate OT vulnerability, asset, configuration, and cyber-risk data from multiple sources. • Develop Python, SQL, and scripting solutions for data extraction, transformation, validation, enrichment, automation, and analysis. • Establish data-quality checks, reconciliation routines, monitoring, alerting, and troubleshooting procedures that improve data completeness, accuracy, timeliness, and reliability. • Identify, assess, track, and report OT cybersecurity risks and vulnerabilities across plant systems and networks, supporting risk-based prioritization and remediation planning. • Develop and maintain Power BI or similar dashboards, reports, metrics, and visualizations that communicate exposure, trends, control coverage, remediation progress, and operational performance. • Translate complex technical and security data into clear insights and recommendations for plant teams, cybersecurity stakeholders, manufacturing leadership, and technology partners. • Partner with cybersecurity, manufacturing engineering, plant operations, data engineering, and technology teams to define requirements, resolve data issues, and deliver cross-functional solutions. • Document data sources, data models, pipeline logic, controls, lineage, operating procedures, and troubleshooting guidance in a clear and maintainable format. • Automate repeatable data preparation, analysis, and reporting processes while applying appropriate security, privacy, access-control, and data-governance practices. • Propose and deliver process improvements that increase visibility, reduce manual effort, improve reporting consistency, and strengthen OT vulnerability management. • Communicate status, risks, dependencies, findings, and recommendations clearly; follow issues through resolution and escalate potential impacts early. Your Skills & Abilities (Required Qualifications) • Bachelor’s degree in Computer Science, Cybersecurity, Information Technology, Data Engineering, Engineering, or a related field, or equivalent relevant experience. • 3+ years of professional experience in cybersecurity, data engineering, analytics, software engineering, manufacturing technology, or a related field. • Hands-on experience developing and supporting production data pipelines using Python, SQL, scripting, ETL, or data-ingestion te