Jobs / United States / Nvidia Corporation
Senior Data and Platform Engineer
Nvidia Corporation · 🇺🇸 5 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 2,374 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 394 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 Nvidia Corporation paid sponsored hires in similar roles701 certified filings for “Engineer Senior Systems Software” (Software Developers) in CA: $173k–$214k, median $190k. Most were filed at wage level IV (82%) — 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 — Nvidia Corporation
The US Department of Labor certified 2,374 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 394 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 Nvidia Corporation →
About the role
NVIDIA’s DGX Cloud organization seeks a Senior Data Platform Engineer to contribute to building the shared data infrastructure that underpins decision-making within DGX Cloud. The DGX Cloud Data Platform transforms infrastructure telemetry and operational data into trustworthy data products for engineering, operations, finance, security, and product teams. These tools aid in monitoring fleet condition, capacity management, utilization tracking, cost oversight, reliability, governance, and the sustained expansion of large GPU fleets across cloud service providers and NVIDIA Cloud Partners. We would love for you to apply today! What you'll be doing: • Define and guide the technical vision for a key DGX Cloud Data Platform domain covering various services, pipelines, data products, and consumer teams. Take responsibility for its architecture, interfaces, and growth, while foreseeing needs related to scale, reliability, performance, security, compatibility, and cost. • Lead the technical delivery of complex, cross-team initiatives. Transform unclear requirements into well-defined architectures and interfaces, coordinate implementation methods among contributors, personally write essential code, overcome technical obstacles, and guide integrations securely into production. • Architect, implement, and evolve batch and streaming systems that ingest, transform, reconcile, and serve fleet, capacity, utilization, cost, scheduling, and operational telemetry at scale across multiple environments and consumers. • Build shared platform capabilities—including libraries, workflow and orchestration abstractions, deployment tooling, and implementation standards—that are adopted across teams and measurably improve delivery speed, reliability, operational effort, and cost. • Serve as the technical lead for high-impact production investigations spanning pipelines, applications, query engines, distributed processing, storage, networks, and cloud services. Coordinate across owners, establish root cause, drive durable resolution, and ensure preventive improvements are implemented. • Establish and drive adoption of engineering standards for automated testing, data quality, reconciliation, lineage, service-level objectives, observability, secure service identities, least-privilege access, release readiness, and auditable deployments. • Establish robust data models, semantics, ownership boundaries, and serving interfaces across teams. Provide tables, APIs, automation, dashboards, and internal applications that ensure trusted DGX Cloud data is widely accessible without sacrificing accuracy or maintainability. • Provide technical leadership through architecture and build reviews, hands-on mentorship of senior engineers, and evidence-based resolution of difficult tradeoffs. Raise engineering quality across teams through reusable patterns, clear decisions, and sustained follow-through. What we need to see: • 8+ years of relevant industry experience with a Bachelor’s or equivalent experience, and a Master’s degree or equivalent experience in Computer Science, Engineering, or a related field. • A sustained record of personally crafting, implementing, and operating production software, data platforms, databases, or distributed systems. This includes end-to-end technical ownership of a multi-system platform domain or a complex cross-team engineering initiative. • Experience includes deep hands-on work with distributed processing, analytical or relational databases, production ETL, change-data capture, streaming or event processing, or backend and cloud systems handling large data volumes. • Strong software engineering fundamentals and production proficiency in a backend or systems language, with deep experience using data-processing and platform libra