Analytics Engineer Jobs at NVIDIA with Visa Sponsorship
Analytics Engineer jobs at NVIDIA sit at the intersection of data infrastructure and business intelligence, supporting teams that build the systems powering AI and accelerated computing. NVIDIA has a strong track record of sponsoring international talent for this function, making it a realistic target for visa-dependent candidates with the right technical foundation.
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NVIDIA's Developer Technology Engineering team is a global network of world-class experts pushing the boundaries of accelerated computing! We empower developers with groundbreaking solutions while driving innovation that fuels NVIDIA's leadership in this transformative field. NVIDIA's accelerated computing platform is revolutionizing industries. To capitalize on this explosive growth, we're growing our team and seeking a visionary leader to drive our continued success.
What you’ll be doing:
This role offers a unique opportunity to lead a team of skilled performance engineers collaborating directly with the developer community to unlock the full potential of NVIDIA's groundbreaking CPUs and GPUs! NVIDIA platform is known for its AI dominance in deep learning training and inference. Nonetheless, modern data centers have hundreds of millions of CPUs that are used today to run mission critical workloads such as database, data preprocessing, compression, video transcoding, web servers, and many others. Help modernize today’s data centers by researching and developing implementations to help save cost and power using the advanced NVIDIA platform. Core responsibilities include:
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Driving Innovation: This involves researching, analyzing, and developing innovative techniques to optimize performance of complex workloads across cloud and on-premise environments. These workloads are difficult to parallelize and major performance speed-ups require inventing new algorithms and working side-by-side with architects to influence hardware.
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Technical Leadership: Drive technical excellence by leading software design decisions, influencing architecture roadmap, and effectively communicating technical solutions to multi-functional teams. Prioritize and lead key initiatives that advance the performance and adoption of NVIDIA’s hardware and software platforms.
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Growing and Mentoring Your Team: Build a distributed world-class team of performance engineers. Grow domain, hardware and software expertise within your team to strengthen external developer engagements. Foster a collaborative and innovative culture that encourages idea sharing, empowers team members, and provides opportunities for professional growth.
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Collaboration and Communication: Collaborate closely with company leadership, research teams, and cross-functional partners to drive strategic decision-making, program management, and successful initiative implementation. Advocate for next-generation hardware and software products that address the evolving needs of the developer community.
What we need to see:
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An MS or PhD in Computer Science, Computer Engineering, or in a related computationally focused science degree (or equivalent experience).
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7+ overall years of relevant experience with 4+ years in a technical role and 3+ years of experience in an engineering leadership role.
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Outstanding leadership, strong cross-functional collaboration, and impactful project execution.
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Hands-on experience in low-level performance optimization, including GPU parallel programming, e.g., CUDA.
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Programming fluency in C/C++ with a deep understanding of algorithms and software development.
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In-depth expertise with CPU and GPU architecture fundamentals.
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Strong algorithmic skills and proven experience implementing low-level optimizations for enterprise applications.
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A track record of building high-performing teams by attracting and hiring top engineering talent.
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Excellent communication and presentation skills.
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Demonstrated ability to successfully plan, lead, and execute high-impact initiatives.
Ways to stand out from the crowd:
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A PhD in a relevant field is highly valued.
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Experience leading engineering teams to design performance-first prototypes.
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Strong background in distributed high-performance data analytics including SQL or vector databases.
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Expertise in modern data center network and storage technologies.
NVIDIA is widely considered to be one of the technology industry's most desirable employers. We have some of the most forward-thinking and hardworking people in the world working with us. Come join our team of brilliant minds leading the way in accelerated computing. Are you a creative and independent computer scientist with a passion for parallel computing? If so, we invite you to apply.
LI-Hybrid
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 224,000 USD - 356,500 USD for Level 3, and 272,000 USD - 431,250 USD for Level 4.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until March 21, 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.
Tips for Finding Analytics Engineer Jobs at NVIDIA
Align your portfolio to NVIDIA's data stack
NVIDIA's Analytics Engineer roles consistently require experience with dbt, Snowflake, and large-scale pipeline orchestration. Before applying, build or document projects that reflect those tools. A portfolio gap here gets flagged early in technical screens.
Target NVIDIA's enterprise data and AI divisions
Analytics Engineer openings at NVIDIA cluster around teams supporting go-to-market, revenue operations, and AI infrastructure. Filtering by these business units when searching improves match quality and puts you in front of hiring managers who budget for sponsorship.
Clarify your visa type before the offer stage
NVIDIA sponsors both H-1B and E-3 visas for this role. If you're Australian, the E-3 has no lottery and can move faster. Knowing which pathway applies to you before recruiter calls prevents mismatch and signals you understand the process.
Use Migrate Mate to surface NVIDIA's open Analytics Engineer roles
Analytics Engineer positions at NVIDIA don't all carry the same title. Migrate Mate filters job listings by visa sponsorship history and role type, so you can find active openings that match your background without sorting through listings that won't support your status.
Prepare your specialty occupation documentation early
USCIS scrutinizes Analytics Engineer petitions because the role name spans a wide range of duties. Gather transcripts, degree evaluations, and any employer letters that tie your specific degree field to the data engineering responsibilities in your offer letter before the I-129 is filed.
Ask about NVIDIA's LCA filing timeline during negotiation
Your start date depends on DOL certifying the Labor Condition Application before USCIS can process the H-1B petition. NVIDIA's recruiting team typically coordinates this, but confirming the expected LCA filing date protects you from a start date that slips past your current status expiry.
Frequently Asked Questions
Does NVIDIA sponsor H-1B visas for Analytics Engineers?
Yes, NVIDIA sponsors H-1B visas for Analytics Engineer roles. NVIDIA participates in the annual H-1B lottery each April, so new sponsorships for cap-subject candidates are tied to that cycle. If you're already H-1B visa exempt or transferring from another employer, NVIDIA can file a transfer petition at any point in the year without waiting for the lottery.
How do I apply for Analytics Engineer jobs at NVIDIA?
Applications go through NVIDIA's careers portal. Roles are listed under titles like Analytics Engineer, Senior Analytics Engineer, and Data Analytics Engineer depending on seniority and team. Migrate Mate aggregates NVIDIA's open Analytics Engineer positions filtered by visa sponsorship eligibility, which can save time if you need to confirm a role supports your visa type before applying.
Which visa types does NVIDIA commonly sponsor for Analytics Engineer roles?
NVIDIA sponsors H-1B visas most broadly for this function, which covers the widest range of nationalities. Australian citizens can pursue the E-3 visa instead, which has a separate annual allocation and no lottery, making it a faster path in most years. NVIDIA also supports Green Card sponsorship through the EB-2 and EB-3 employment-based categories for longer-tenured employees.
What qualifications does NVIDIA expect for Analytics Engineer candidates?
Most Analytics Engineer roles at NVIDIA require a bachelor's degree or higher in computer science, statistics, engineering, or a closely related quantitative field. USCIS requires the degree to directly relate to the job duties for specialty occupation classification, so a degree in a loosely related field can complicate the petition. Hands-on experience with dbt, SQL, and cloud data warehouses like Snowflake or BigQuery is consistently expected across posted roles.
How do I navigate the timeline between an offer and my first day at NVIDIA?
For H-1B transfers, NVIDIA can typically file as soon as you have an offer, and you can start once USCIS issues a receipt notice if you're already in valid H-1B status. For new cap-subject petitions, the earliest possible start date after an April lottery selection is October 1. For E-3 visa applicants, the timeline is shorter since you apply directly at a U.S. consulate and can receive the visa stamp within a few weeks of the interview.