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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Get Access To All JobsINTRODUCTION
NVIDIA is seeking a high-caliber, hands-on data engineer specializing in supply chain to act as the ultimate data custodian. This person will build the foundation for our fully coordinated forecasting and supply chain ecosystem. In this critical role, you will form a tight team with our Principal Modeling Engineer and report directly into executive leadership. Your mission is to replace manual workflows with automated, production-grade data pipelines. You will personally compose, curate, and maintain the massive datasets—encompassing semiconductor wafers, memory, substrates, and critical long-lead-time sub-assemblies—that feed our multi-billion-dollar simulation engines. Are you excited about this mission? If you are an absolute data purist who loves building bulletproof pipelines and wants to see your infrastructure directly drive unified planning decisions from data to execution, this is your role!
ROLE AND RESPONSIBILITIES
What You’ll Be Doing
- Personally compose, write, and scale automated data pipelines using SQL and Python to extract, transform, and load large supply chain datasets from internal and external systems.
- Data Curation & Cleanliness: Serve as the primary guardian of data quality. Build automated validation scripts to catch anomalies, missing inputs, and historical mismatches before they enter our advanced planning frameworks.
- Build and improve automated pipelines that feed downstream machine learning and AI models. Make sure data is clean, low-latency, and accurately prepared for advanced computation.
- Infrastructure Management: Architect and maintain highly optimized data tables, views, and schemas specifically structured for rapid querying by our unified computational systems.
- Systems Deconstruction: Partner with the team to deconstruct legacy, decentralized planning workflows and systematically migrate them into automated, centralized data environments that tie forecasting directly to procurement.
- Cross-Functional Collaboration: Sync closely with engineering, global procurement, operations, and IT teams to unearth hidden data sources and standardize core supply chain metrics.
BASIC QUALIFICATIONS
- Bachelor’s degree in Computer Science, Data Engineering, Information Systems, Industrial Engineering, Operations Research, or equivalent experience.
- Expert Data Engineering Skills: Mastery in SQL and Python (specifically data manipulation libraries like Pandas) is non-negotiable.
- 7+ Years of Data Pipeline Experience: Proven track record of personally building and running automated ETL/ELT pipelines in a production setting.
- Database Expertise: Deep experience working with relational databases, data warehouses (e.g., Snowflake, BigQuery), or large enterprise ERP systems (like SAP or Oracle).
- Extreme Detail Orientation: A hyper-focused mindset regarding data integrity; you are someone who finds a missing cell or a formatting glitch in a million-row dataset satisfying to solve.
- High Autonomy: Comfortable operating with loose initial guidelines to build robust, production-ready data pipelines from scratch.
PREFERRED QUALIFICATIONS
- Prior experience building data infrastructure within the semiconductor, electronics, or large-scale technology hardware supply chains.
- Background with mathematical modeling environments, advanced computation engines, or algorithmic simulation software (e.g., MATLAB, advanced Python packages).
- Familiarity with workflow orchestration tools (like Apache Airflow or dbt) or basic infrastructure used to support Machine Learning pipelines (DataOps).
- Experience cloud-architecting supply chain master data (AWS, Azure, GCP).
COMPENSATION
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 230,000 USD for Level 4, and 184,000 USD - 287,500 USD for Level 5. You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until July 14, 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.
INTRODUCTION
NVIDIA is seeking a high-caliber, hands-on data engineer specializing in supply chain to act as the ultimate data custodian. This person will build the foundation for our fully coordinated forecasting and supply chain ecosystem. In this critical role, you will form a tight team with our Principal Modeling Engineer and report directly into executive leadership. Your mission is to replace manual workflows with automated, production-grade data pipelines. You will personally compose, curate, and maintain the massive datasets—encompassing semiconductor wafers, memory, substrates, and critical long-lead-time sub-assemblies—that feed our multi-billion-dollar simulation engines. Are you excited about this mission? If you are an absolute data purist who loves building bulletproof pipelines and wants to see your infrastructure directly drive unified planning decisions from data to execution, this is your role!
ROLE AND RESPONSIBILITIES
What You’ll Be Doing
- Personally compose, write, and scale automated data pipelines using SQL and Python to extract, transform, and load large supply chain datasets from internal and external systems.
- Data Curation & Cleanliness: Serve as the primary guardian of data quality. Build automated validation scripts to catch anomalies, missing inputs, and historical mismatches before they enter our advanced planning frameworks.
- Build and improve automated pipelines that feed downstream machine learning and AI models. Make sure data is clean, low-latency, and accurately prepared for advanced computation.
- Infrastructure Management: Architect and maintain highly optimized data tables, views, and schemas specifically structured for rapid querying by our unified computational systems.
- Systems Deconstruction: Partner with the team to deconstruct legacy, decentralized planning workflows and systematically migrate them into automated, centralized data environments that tie forecasting directly to procurement.
- Cross-Functional Collaboration: Sync closely with engineering, global procurement, operations, and IT teams to unearth hidden data sources and standardize core supply chain metrics.
BASIC QUALIFICATIONS
- Bachelor’s degree in Computer Science, Data Engineering, Information Systems, Industrial Engineering, Operations Research, or equivalent experience.
- Expert Data Engineering Skills: Mastery in SQL and Python (specifically data manipulation libraries like Pandas) is non-negotiable.
- 7+ Years of Data Pipeline Experience: Proven track record of personally building and running automated ETL/ELT pipelines in a production setting.
- Database Expertise: Deep experience working with relational databases, data warehouses (e.g., Snowflake, BigQuery), or large enterprise ERP systems (like SAP or Oracle).
- Extreme Detail Orientation: A hyper-focused mindset regarding data integrity; you are someone who finds a missing cell or a formatting glitch in a million-row dataset satisfying to solve.
- High Autonomy: Comfortable operating with loose initial guidelines to build robust, production-ready data pipelines from scratch.
PREFERRED QUALIFICATIONS
- Prior experience building data infrastructure within the semiconductor, electronics, or large-scale technology hardware supply chains.
- Background with mathematical modeling environments, advanced computation engines, or algorithmic simulation software (e.g., MATLAB, advanced Python packages).
- Familiarity with workflow orchestration tools (like Apache Airflow or dbt) or basic infrastructure used to support Machine Learning pipelines (DataOps).
- Experience cloud-architecting supply chain master data (AWS, Azure, GCP).
COMPENSATION
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 230,000 USD for Level 4, and 184,000 USD - 287,500 USD for Level 5. You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until July 14, 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.
See all Data Engineer Jobs at NVIDIA
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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.