Data Engineer Jobs at NVIDIA with Visa Sponsorship
NVIDIA's Data Engineer roles 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 JobsNVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.
NVIDIA is hiring a Data Engineer within the Finance AI and Data Science team. We are looking for an experienced Data Engineer to constantly innovate and turn complex challenges into high-performance pipelines that power our traditional analytics and modern agentic AI. Your role will involve ingesting and processing unstructured documents into our data platform, working closely with AI developers and finance experts to develop strong, scalable data products that convert raw text into actionable intelligence.
What you'll be doing:
- Build and optimize pipelines that extract insights from complex financial documents like SEC filings, contracts, and tax reports. Use innovative tools and techniques to help humans and AI agents search and perform multi-step reasoning across different document types.
- Combine business insight and the data engineering toolkit to support critical business process automation, BI, data science, and AI initiatives.
- Trace data workflows to source systems, then develop and deploy accurate and optimized data pipelines, using modern scheduling, automation, and data orchestration tools.
- Develop deep knowledge of financial data and requirements, working directly with collaborators and owning projects end-to-end on a diverse set of finance and finance-adjacent data sets.
- Integrate AI into data workflows, applying sensible and secure agentic models as a core component of our data framework.
- Deliver an audit-ready source of truth by implementing strict data quality and lineage standards, ensuring all technical solutions translate into clear, actionable insights for collaborators.
What we need to see:
- Bachelor's or Master’s in a quantitative field such as Statistics, Computer Science, Business Analytics, Data Science, Economics, or equivalent experience.
- 5+ years of experience, with at least 4 years in data engineering.
- ETL/ELT experience in modern Data Platforms such as Snowflake, Databricks, or AWS/Azure/GCP equivalents is required. Experience with Git and building and maintaining CI/CD pipelines is also needed. Familiarity with orchestrators like Airflow and testing tools like pytest or Great Expectations is important.
- Ability to write readable and maintainable code (primarily in SQL, Python/PySpark), knowledge of scientific libraries for data processing (Numpy, SciPy, Pandas).
- Experience collaborating with IT, InfoSec, business partners, and data scientists to build end-to-end data pipelines that ensure data accuracy and quality across relational databases, data lakes, and warehouses.
- A passion for data engineering backed by a basic understanding of statistics and machine learning, with the communication skills necessary to translate technical status to diverse collaborators.
Ways to stand out from the crowd:
- Experience with SAP and/or Salesforce.
- Practical experience building and deploying Graph-RAG and similar systems, using a wide variety of data formats (e.g., JSON, XML, PDF, Word, Excel, PowerPoint, etc.).
- Experience assisting a data science group centered on business functions (finance, sales ops, HR, marketing, supply chain, etc.).
- Experience with app development frameworks like Flask and/or Streamlit, data versioning tools like DVC, and data processing tools like dbc.
- Familiarity with regulated data, and building pipelines with compliance requirements.
Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family.
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 3, and 168,000 USD - 264,500 USD for Level 4. You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until April 26, 2026. This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering a diverse 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.
NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.
NVIDIA is hiring a Data Engineer within the Finance AI and Data Science team. We are looking for an experienced Data Engineer to constantly innovate and turn complex challenges into high-performance pipelines that power our traditional analytics and modern agentic AI. Your role will involve ingesting and processing unstructured documents into our data platform, working closely with AI developers and finance experts to develop strong, scalable data products that convert raw text into actionable intelligence.
What you'll be doing:
- Build and optimize pipelines that extract insights from complex financial documents like SEC filings, contracts, and tax reports. Use innovative tools and techniques to help humans and AI agents search and perform multi-step reasoning across different document types.
- Combine business insight and the data engineering toolkit to support critical business process automation, BI, data science, and AI initiatives.
- Trace data workflows to source systems, then develop and deploy accurate and optimized data pipelines, using modern scheduling, automation, and data orchestration tools.
- Develop deep knowledge of financial data and requirements, working directly with collaborators and owning projects end-to-end on a diverse set of finance and finance-adjacent data sets.
- Integrate AI into data workflows, applying sensible and secure agentic models as a core component of our data framework.
- Deliver an audit-ready source of truth by implementing strict data quality and lineage standards, ensuring all technical solutions translate into clear, actionable insights for collaborators.
What we need to see:
- Bachelor's or Master’s in a quantitative field such as Statistics, Computer Science, Business Analytics, Data Science, Economics, or equivalent experience.
- 5+ years of experience, with at least 4 years in data engineering.
- ETL/ELT experience in modern Data Platforms such as Snowflake, Databricks, or AWS/Azure/GCP equivalents is required. Experience with Git and building and maintaining CI/CD pipelines is also needed. Familiarity with orchestrators like Airflow and testing tools like pytest or Great Expectations is important.
- Ability to write readable and maintainable code (primarily in SQL, Python/PySpark), knowledge of scientific libraries for data processing (Numpy, SciPy, Pandas).
- Experience collaborating with IT, InfoSec, business partners, and data scientists to build end-to-end data pipelines that ensure data accuracy and quality across relational databases, data lakes, and warehouses.
- A passion for data engineering backed by a basic understanding of statistics and machine learning, with the communication skills necessary to translate technical status to diverse collaborators.
Ways to stand out from the crowd:
- Experience with SAP and/or Salesforce.
- Practical experience building and deploying Graph-RAG and similar systems, using a wide variety of data formats (e.g., JSON, XML, PDF, Word, Excel, PowerPoint, etc.).
- Experience assisting a data science group centered on business functions (finance, sales ops, HR, marketing, supply chain, etc.).
- Experience with app development frameworks like Flask and/or Streamlit, data versioning tools like DVC, and data processing tools like dbc.
- Familiarity with regulated data, and building pipelines with compliance requirements.
Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family.
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 3, and 168,000 USD - 264,500 USD for Level 4. You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until April 26, 2026. This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering a diverse 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 159+ Data Engineer at NVIDIA jobs
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Get Access To All JobsTips for Finding Data Engineer Jobs at NVIDIA Jobs
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.
Data Engineer at NVIDIA jobs are hiring across the US. Find yours.
Find Data Engineer at NVIDIA JobsFrequently 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, and Green Card pathways including EB-2 and EB-3 for Data Engineers. Australian citizens can use the E-3, 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.
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