Data Analytics Engineer Jobs at NVIDIA with Visa Sponsorship
Data Analytics Engineer jobs at NVIDIA sit at the intersection of large-scale data infrastructure and product intelligence, supporting GPU computing, AI platforms, and enterprise solutions. NVIDIA has a consistent track record of sponsoring international talent in technical engineering functions, making it a realistic target for H-1B visa and E-3 visa applicants.
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Get Access To All JobsINTRODUCTION
We're building a new generation of data center CPUs at NVIDIA — Vera, Grace, and future designs purpose-built for accelerated computing and the workloads defining infrastructure. Data analytics is one of the highest-value arenas for CPU performance, and we need someone to own NVIDIA's strategy and value proposition there! This role sits at the nexus of go-to-market, software architecture, platform architecture, performance measurement, and competitive positioning — making it a true workload strategy role, not a benchmark-running one. From TPC-H and TPC-DS methodologies to collaborative solutions with the world's leading database and analytics vendors, the scope is broad and the impact is real. We're looking for a product manager who deeply understands how CPUs win in practice and can turn that insight into roadmap decisions, customer proof points, and field-ready positioning.
ROLE AND RESPONSIBILITIES:
- Taking responsibility for the workload and market approach for data analytics and data processing on NVIDIA data center CPUs — identifying priority workloads, customer scenarios, and the benchmarks and proof points that should guide the roadmap.
- Leading the complete lifecycle of benchmarks like TPC-H and TPC-DS: methodology, cluster and benchmarking architecture, competitive analysis, and market positioning.
- Translating disk, cache, memory, I/O, clustering, availability, and software behavior into concrete CPU, platform, and system requirements. Then advising architecture and platform teams on what to build and why.
- Building the quantitative value proposition across performance, infrastructure, software licensing, power, and TCO to position NVIDIA CPUs against challenging architectures.
- Working alongside external ISVs, database and analytics vendors, cloud providers, and strategic customers to verify requirements and build joint solutions and go-to-market approaches.
- Redefining benchmark results and customer evidence into product decisions, competitive reactions, customer proof points, and field enablement materials.
BASIC QUALIFICATIONS:
- 12+ years of experience in technical product management, performance engineering, or a closely related area.
- BS or MS in Computer Science, Electrical or Computer Engineering — or equivalent experience.
- Comprehensive, practical knowledge of CPU and database performance.
- Understanding of system hardware characteristics that influence analytics performance — caching and clustering methods, high availability, memory and I/O sensitivity, and architectural trade-offs.
- Ability to influence platform and architecture teams by translating workload performance into product, platform, and feature requirements.
- Experience collaborating with external ISVs, silicon vendors, or the broader analytics ecosystem.
PREFERRED QUALIFICATIONS:
- Hands-on experience with TPC-H, TPC-DS, or comparable data analytics benchmarks, including methodology development and measurement.
- Understanding of the disk, cache, and memory sensitivities of database and analytics workloads at scale.
- Experience with market entry strategies, solution presentation, or the wider data analytics provider and cloud environment.
- Background in accelerated computing platforms or data center CPU product launches.
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 184,000 USD - 287,500 USD for Level 5, and 224,000 USD - 356,500 USD for Level 6.
- You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until October 19, 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
We're building a new generation of data center CPUs at NVIDIA — Vera, Grace, and future designs purpose-built for accelerated computing and the workloads defining infrastructure. Data analytics is one of the highest-value arenas for CPU performance, and we need someone to own NVIDIA's strategy and value proposition there! This role sits at the nexus of go-to-market, software architecture, platform architecture, performance measurement, and competitive positioning — making it a true workload strategy role, not a benchmark-running one. From TPC-H and TPC-DS methodologies to collaborative solutions with the world's leading database and analytics vendors, the scope is broad and the impact is real. We're looking for a product manager who deeply understands how CPUs win in practice and can turn that insight into roadmap decisions, customer proof points, and field-ready positioning.
ROLE AND RESPONSIBILITIES:
- Taking responsibility for the workload and market approach for data analytics and data processing on NVIDIA data center CPUs — identifying priority workloads, customer scenarios, and the benchmarks and proof points that should guide the roadmap.
- Leading the complete lifecycle of benchmarks like TPC-H and TPC-DS: methodology, cluster and benchmarking architecture, competitive analysis, and market positioning.
- Translating disk, cache, memory, I/O, clustering, availability, and software behavior into concrete CPU, platform, and system requirements. Then advising architecture and platform teams on what to build and why.
- Building the quantitative value proposition across performance, infrastructure, software licensing, power, and TCO to position NVIDIA CPUs against challenging architectures.
- Working alongside external ISVs, database and analytics vendors, cloud providers, and strategic customers to verify requirements and build joint solutions and go-to-market approaches.
- Redefining benchmark results and customer evidence into product decisions, competitive reactions, customer proof points, and field enablement materials.
BASIC QUALIFICATIONS:
- 12+ years of experience in technical product management, performance engineering, or a closely related area.
- BS or MS in Computer Science, Electrical or Computer Engineering — or equivalent experience.
- Comprehensive, practical knowledge of CPU and database performance.
- Understanding of system hardware characteristics that influence analytics performance — caching and clustering methods, high availability, memory and I/O sensitivity, and architectural trade-offs.
- Ability to influence platform and architecture teams by translating workload performance into product, platform, and feature requirements.
- Experience collaborating with external ISVs, silicon vendors, or the broader analytics ecosystem.
PREFERRED QUALIFICATIONS:
- Hands-on experience with TPC-H, TPC-DS, or comparable data analytics benchmarks, including methodology development and measurement.
- Understanding of the disk, cache, and memory sensitivities of database and analytics workloads at scale.
- Experience with market entry strategies, solution presentation, or the wider data analytics provider and cloud environment.
- Background in accelerated computing platforms or data center CPU product launches.
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 184,000 USD - 287,500 USD for Level 5, and 224,000 USD - 356,500 USD for Level 6.
- You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until October 19, 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 Analytics Engineer Jobs at NVIDIA
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Data Analytics Engineer Jobs at NVIDIA.
Get Access To All JobsTips for Finding Data Analytics Engineer Jobs at NVIDIA
Align Your Portfolio to NVIDIA's Data Stack
NVIDIA's Data Analytics Engineering roles frequently involve pipelines built on Spark, dbt, and cloud-native warehouses like Snowflake or BigQuery. Frame your portfolio projects around GPU-accelerated analytics or AI-adjacent data workflows to signal direct relevance before your application lands with a recruiter.
Target Roles Listed Under Hardware and Platform Divisions
NVIDIA posts Data Analytics Engineer openings across multiple internal divisions. Roles tied to GeForce, CUDA, or enterprise AI platforms tend to have longer hiring cycles but stronger sponsorship intent, since they sit within established headcount plans rather than exploratory team builds.
Confirm Specialty Occupation Standing for Your Degree
H-1B eligibility requires your role to qualify as a specialty occupation under USCIS standards, meaning a specific bachelor's degree field is normally the minimum entry requirement. If your degree is in a tangential field like applied mathematics or statistics, gather documentation showing direct relevance to the Data Analytics Engineer job description before the offer stage.
Negotiate Offer Timing Around the H-1B Cap Calendar
USCIS opens H-1B registration each March for an October 1 start date. If you receive an offer outside that window, ask NVIDIA's immigration team early whether a cap-exempt pathway or a change-of-status bridge on a current visa applies to your situation.
Use Migrate Mate to Filter Open Roles by Visa Type
NVIDIA maintains a large number of active Data Analytics Engineer openings at any given time. Use Migrate Mate to filter specifically for positions tagged to H-1B or E-3 sponsorship, so you're only investing preparation time in roles where your visa pathway is already supported.
Prepare for a Technical Loop Before Immigration Discussions Begin
NVIDIA's interview process for analytics engineering roles typically includes SQL and data modeling assessments alongside system design questions. Immigration and sponsorship conversations happen after the technical loop clears, so demonstrate technical depth first rather than raising visa logistics in early recruiter screens.
Frequently Asked Questions
Does NVIDIA sponsor H-1B visas for Data Analytics Engineers?
Yes, NVIDIA sponsors H-1B visas for Data Analytics Engineer roles. The company works with immigration counsel to file petitions through the standard USCIS cap process each spring, with an October 1 employment start date. If you're already on a valid status like F-1 OPT or L-1 visa, NVIDIA can also support a change of status rather than requiring consular processing.
How do I apply for Data Analytics Engineer jobs at NVIDIA?
Applications go through NVIDIA's careers portal at nvidia.com/en-us/about-nvidia/careers. Search for Data Analytics Engineer and filter by location or team. Tailor your resume to reflect data pipeline experience, analytical tooling relevant to NVIDIA's stack, and any GPU or AI-adjacent project work. You can also browse verified sponsorship-tagged openings on Migrate Mate to identify which postings actively support international candidates.
Which visa types does NVIDIA commonly use for Data Analytics Engineer roles?
NVIDIA sponsors H-1B visas most frequently for Data Analytics Engineers, which covers the broadest pool of international applicants. Australian citizens are eligible for the E-3 visa, which bypasses the H-1B lottery and follows a similar specialty occupation standard. For longer-term pathways, NVIDIA also supports Green Card sponsorship through EB-2 and EB-3 classifications, typically initiated after an employee has been with the company for some time.
What qualifications and experience does NVIDIA expect for Data Analytics Engineers?
NVIDIA typically expects a bachelor's degree or higher in computer science, data engineering, statistics, or a closely related field. Hands-on experience with SQL, Python, and at least one cloud data warehouse platform is standard. Roles that sit closer to the AI infrastructure side of the business often expect familiarity with large-scale data pipelines, ETL orchestration tools like Airflow, and some exposure to GPU computing environments or ML data workflows.
How do I navigate the timeline between offer and visa filing at NVIDIA?
The critical window is USCIS's H-1B registration period, which opens in early March each year. NVIDIA's immigration team needs to register your petition before that deadline for an October 1 start. If you receive your offer after registration closes, discuss bridge options with your recruiter, including whether your current F-1 OPT or another status allows you to begin work while the next cap cycle opens.