Cloud Data Engineer Jobs at NVIDIA with Visa Sponsorship
NVIDIA hires Cloud Data Engineers to build and scale the infrastructure behind its AI and accelerated computing platforms. The company has a consistent track record of sponsoring work visas for technical roles in this function, making it a realistic target if you're planning your move to the U.S.
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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 for the Finance AI and Data Science team. We seek an experienced Data Engineer to continuously create and improve high-performance pipelines. These pipelines support both our traditional analytics and modern AI. You will collaborate with AI developers and finance professionals to develop robust, scalable data products and communicate technical solutions clearly across the organization.
What you'll be doing:
- Combine business insight and the data engineering toolkit to support critical business process automation, BI, data science, and agentic AI initiatives.
- Trace complex 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 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 degree in a quantitative field (e.g. Statistics, Computer Science, Business Analytics, Data Science, Economics, or a related area) or equivalent experience.
- 5+ years of experience, including at least 4 years specifically in data engineering.
- ETL/ELT experience in modern Data Platforms such as Snowflake, Databricks, or AWS/Azure/GCP equivalents is required. Experience with Git, building and maintaining CI/CD pipelines, and using an orchestrator (e.g., Airflow) is also needed. Familiarity with 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.
- Background with non-tabular data formats (JSON, XML, PDF, Excel, PowerPoint, etc.), APIs and other non-traditional data sources.
- Experience supporting a business focused data science team (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 for the Finance AI and Data Science team. We seek an experienced Data Engineer to continuously create and improve high-performance pipelines. These pipelines support both our traditional analytics and modern AI. You will collaborate with AI developers and finance professionals to develop robust, scalable data products and communicate technical solutions clearly across the organization.
What you'll be doing:
- Combine business insight and the data engineering toolkit to support critical business process automation, BI, data science, and agentic AI initiatives.
- Trace complex 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 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 degree in a quantitative field (e.g. Statistics, Computer Science, Business Analytics, Data Science, Economics, or a related area) or equivalent experience.
- 5+ years of experience, including at least 4 years specifically in data engineering.
- ETL/ELT experience in modern Data Platforms such as Snowflake, Databricks, or AWS/Azure/GCP equivalents is required. Experience with Git, building and maintaining CI/CD pipelines, and using an orchestrator (e.g., Airflow) is also needed. Familiarity with 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.
- Background with non-tabular data formats (JSON, XML, PDF, Excel, PowerPoint, etc.), APIs and other non-traditional data sources.
- Experience supporting a business focused data science team (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.
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Get Access To All JobsTips for Finding Cloud Data Engineer Jobs at NVIDIA Jobs
Align your portfolio with GPU-accelerated workflows
NVIDIA's Cloud Data Engineer roles increasingly require experience with GPU-accelerated data pipelines and distributed compute frameworks. Before applying, build or document projects using CUDA-adjacent tooling, Spark on GPU clusters, or cloud platforms like AWS, GCP, or Azure at scale.
Target roles tied to NVIDIA's cloud partnerships
NVIDIA's cloud engineering work often sits at the intersection of its partnerships with hyperscalers. Roles supporting NVIDIA DGX Cloud or AI Enterprise tend to have clearer sponsorship pathways because they require specialized skills that are harder to source domestically.
Get your credentials documented before the offer stage
NVIDIA's legal team will need your degree transcripts and employment history to support the H-1B specialty occupation determination. If your degree is from outside the U.S., get a credential evaluation from a NACES-approved agency before you reach the offer stage, not after.
Understand how NVIDIA's H-1B cap timing affects you
If you're not already in H-1B status, NVIDIA can only file a new cap-subject petition during the USCIS registration window each March. Map your job search backward from that window so an offer can be secured in time to register.
Use Migrate Mate to filter open Cloud Data Engineer roles
Sponsorship-eligible listings at NVIDIA are easy to miss on general job boards. Use Migrate Mate to filter Cloud Data Engineer openings at NVIDIA by visa type so you're only spending time on roles where sponsorship is actually on the table.
Confirm LCA wage level matches your experience tier
NVIDIA files a Labor Condition Application with the DOL before your H-1B petition. The prevailing wage level on that LCA must match your role and experience. If you're being offered a Level 1 wage for a senior-scope role, flag it with your immigration attorney before signing.
Cloud Data Engineer at NVIDIA jobs are hiring across the US. Find yours.
Find Cloud Data Engineer at NVIDIA JobsFrequently Asked Questions
Does NVIDIA sponsor H-1B visas for Cloud Data Engineers?
Yes, NVIDIA sponsors H-1B visas for Cloud Data Engineer roles. The process requires NVIDIA's legal team to file a Labor Condition Application with the DOL, followed by an H-1B petition with USCIS. If you're not already in H-1B status, timing your offer around the annual March registration window is critical to avoid a full year's delay.
Which visa types does NVIDIA commonly use for Cloud Data Engineer roles?
NVIDIA sponsors H-1B visas for most Cloud Data Engineer hires, along with the E-3 visa for Australian citizens and employment-based Green Cards through the EB-2 and EB-3 categories for longer-term permanent residence. The right visa depends on your nationality, current status, and career timeline. Australian candidates should prioritize the E-3 route given its simpler process and no lottery requirement.
What qualifications does NVIDIA expect for Cloud Data Engineer roles?
NVIDIA typically expects a bachelor's degree or higher in computer science, data engineering, or a closely related field, alongside hands-on experience with large-scale distributed data systems, cloud infrastructure, and pipeline orchestration tools. Familiarity with GPU-accelerated computing environments or NVIDIA's own platform ecosystem is a meaningful differentiator for candidates targeting roles tied to AI infrastructure.
How do I apply for Cloud Data Engineer jobs at NVIDIA?
You can browse and apply for Cloud Data Engineer roles at NVIDIA directly through their careers portal, or use Migrate Mate to surface sponsorship-eligible openings in one place. Before applying, tailor your resume to reflect cloud-scale data infrastructure experience and any exposure to NVIDIA's technology stack. Roles tied to NVIDIA's AI Enterprise or DGX Cloud products tend to have the strongest sponsorship signals.
How do I plan my timeline around NVIDIA's visa sponsorship process?
If you need a new H-1B, USCIS registration opens each March for an October 1 start date, so securing an offer in the first quarter of the year is the practical target. E-3 candidates have more flexibility since there's no lottery, but consulate appointment wait times in Australia can run several weeks. Factor in at least two to three months from offer acceptance to work authorization for most visa types.
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