Data Engineer Jobs at NVIDIA with Visa Sponsorship
Data Engineer jobs at NVIDIA sit at the intersection of large-scale infrastructure and applied AI, spanning data pipeline architecture, warehouse optimization, and platform engineering. NVIDIA has a strong track record of sponsoring work visas for this function, making it a realistic target for international candidates with the right technical background.
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INTRODUCTION
NVIDIA DGX Cloud is the AI supercomputing-as-a-service substrate designed to power the next generation of AI and industrial-scale breakthroughs. As a Security Data Engineer within our Infrastructure Security Engineering organization, you will build the data backbone of our security control plane—the pipelines, lake, and analytics that turn fragmented telemetry from a 250,000+ GPU fleet into a single, queryable, trustworthy picture of security state. Every posture score, every detection, and every autonomous action our platform takes stands on the data foundation you engineer.
What You Will Be Doing:
- Security Data Pipelines: Design, build, and operate the ingestion and transformation pipelines that collect security telemetry and asset inventory from dozens of heterogeneous sources, and normalize them into one canonical model.
- Data Lake & Lakehouse Engineering: Architect and run the storage layer. A data lake/lakehouse built on open formats, with the schema flexibility to absorb structured inventory, semi-structured telemetry, and unstructured logs without constant, breaking migrations.
- Security Analytics & Detection Engineering: Build the query and analytics layer that powers posture scoring, coverage and drift metrics, freshness monitoring, and multi-source correlation.
- Securing the Data Layer Itself: Treat the data platform as a high-value target, because it is. The data you store is a map of every host, every gap, and every credential path. You will engineer encryption at rest and in transit, fine-grained RBAC/ABAC, non-repudiable audit logging, data classification, network isolation, and verifiable retention and purge.
- Data Quality & Trust: Build for stable identity, source attribution, append-only history, and honest coverage. Make a source going quiet a finding, not silence, so that every downstream number comes with a known confidence.
- Multi-Functional Collaboration: Partner with the security control plane team, the inventory systems, identity and endpoint teams, and broader NVIDIA data and security organizations to define data contracts early, so these systems converge by design.
What We Need to See:
We truly recognize that a candidate who checks every single box is simply rare. We aren't looking for a checkbox hire; we are looking for high-caliber engineers with deep spikes of expertise in a few of these areas and the intellectual curiosity to dive into the rest. If your experience aligns with the core of this role—building data systems that are trustworthy at scale—and you can show us how, we want to hear from you!
- Data Engineering at Scale: 15+ years of experience designing, building, and operating production data pipelines, lakes, or lakehouses at high volume and throughput. You build systemic solutions rather than performing manual data wrangling or "tool administration." Bachelor's degree or equivalent.
- Production-Grade Coding: A strong software engineering background with the ability to write clean, maintainable, and well-tested code (e.g., Python, Go, Scala, SQL). You should be comfortable building and operating production data services at scale.
- Data Modeling & Schema Design: Proven ability to design canonical schemas and data models that span many disparate sources and evolve over time without breaking the consumers that depend on them.
- Distributed Data Systems: Hands-on experience with the modern data stacks, both streaming and batch processing, object storage, open table formats, and interactive query engines.
- Security-Minded Data Handling: You design data systems that are themselves defensible. Access control, encryption, audit, and isolation are first-class concerns in your work, and you understand that security data is among the most sensitive data an organization holds.
- Analytics Enablement: A track record of making large, messy datasets genuinely useful—serving interactive analysts, dashboards, and downstream services with data they can trust and query at low latency.
- Foundation: Bachelor's degree in Computer Science, Engineering, or a related technical field (or equivalent experience).
Ways To Stand Out from the Crowd:
- Security Telemetry & Detection Engineering: Experience building SIEM or data-lake detection content, normalizing security logs into common schemas (e.g., OCSF, ECS), or engineering the data layer that feeds correlation and anomaly-detection systems.
- Real-Time & Streaming Data: Expertise building low-latency, near-real-time pipelines where a correlation is only as fast as its slowest input, and detection is measured in minutes.
- HPC/AI Fleet Telemetry: Experience working with GPU and hardware telemetry (DCGM, Redfish/BMC, InfiniBand) or fleet-scale observability across hundreds of thousands of devices.
- AI-Ready Data: Experience engineering the data and feature layers that feed ML or LLM-based reasoning systems, enabling agents to correlate, predict, and act on trustworthy data. How have you made data safe to reason over?
NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. Our work opens up new universes to explore, enables amazing creativity and discovery, and powers what were once science fiction inventions from artificial intelligence to autonomous cars. NVIDIA is looking for great people like you to help us accelerate the next wave of artificial intelligence.
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 272,000 USD - 431,250 USD. You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until June 12, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
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Get Access To All JobsTips for Finding Data Engineer Jobs at NVIDIA
Align your portfolio to NVIDIA's data stack
NVIDIA's Data Engineer roles consistently require experience with distributed systems, ETL pipelines, and cloud platforms like AWS or GCP. Before applying, build or document projects that reflect those tools specifically, not just generic SQL or Python work.
Target teams building internal AI infrastructure
NVIDIA hires Data Engineers across product, research, and enterprise IT. Roles supporting internal AI and GPU platform teams tend to have stronger sponsorship pathways, so filter your search toward those orgs rather than applying broadly across all open positions.
Use Migrate Mate to surface active sponsorship openings
Not every NVIDIA Data Engineer listing will signal sponsorship eligibility upfront. Migrate Mate filters job postings specifically for roles where visa sponsorship is available, saving you from investing time in applications that won't move forward for international candidates.
Request the LCA before your start date
Once NVIDIA extends an offer, confirm that the Labor Condition Application has been certified by DOL before your first day. The LCA must be on file and the prevailing wage must meet your offer, so asking early avoids a last-minute filing delay.
Clarify E-3 eligibility if you hold Australian citizenship
NVIDIA sponsors the E-3 visa, which is available only to Australian citizens. If you qualify, the E-3 avoids the H-1B lottery entirely and can be processed at a U.S. consulate, often faster than a change-of-status petition filed through USCIS.
Document specialized credentials that support EB-2 or EB-3 petitions
For long-term permanent residence, NVIDIA typically pursues PERM-based sponsorship through EB-2 or EB-3. Gather transcripts, performance reviews, and any patents or publications now. PERM labor certification requires detailed records of your qualifications matching the certified job description.
Frequently Asked Questions
Does NVIDIA sponsor H-1B visas for Data Engineers?
Yes, NVIDIA sponsors H-1B visas for Data Engineer roles. Because H-1B is subject to an annual lottery, your application enters the USCIS registration pool each April for an October start date. NVIDIA's legal and HR teams handle the petition process once you clear the lottery, but the timeline means offers typically need to be extended well before the registration window opens in March.
Which visa types does NVIDIA commonly sponsor for Data Engineer roles?
NVIDIA sponsors H-1B, E-3 visa, and Green Card pathways including EB-2 and EB-3 for Data Engineers. Australian citizens can use the E-3 visa, which bypasses the H-1B lottery and allows consular processing. Green Card sponsorship through PERM typically begins after you've established yourself in the role, with EB-2 or EB-3 as the most common routes for this function.
How do I apply for Data Engineer jobs at NVIDIA?
Applications go through NVIDIA's careers portal, where you'll submit a resume tailored to the specific team and stack listed in the job description. For international candidates, Migrate Mate surfaces active NVIDIA Data Engineer roles that include visa sponsorship, so you can focus your time on positions that are actually open to candidates who need work authorization. Technical screens and system design interviews follow the initial application review.
What qualifications does NVIDIA expect for Data Engineer roles?
NVIDIA Data Engineer roles typically require a bachelor's or master's degree in computer science, data engineering, or a related field, along with hands-on experience building scalable data pipelines and working with distributed processing frameworks like Spark or Flink. Familiarity with cloud data warehouses such as Snowflake or BigQuery and experience in Python or Scala are common requirements across postings. Roles closer to AI infrastructure may also expect experience with feature stores or ML pipeline tooling.
How do I plan my timeline when pursuing H-1B sponsorship through NVIDIA?
The H-1B cap year runs on a fixed federal calendar: USCIS opens registration in March, the lottery runs in April, and approved petitions carry an October 1 start date. If you're currently on OPT or another status, coordinate your offer timing with that schedule. USCIS premium processing is available and cuts adjudication to 15 business days, which NVIDIA may elect to use depending on your start date requirements.