NVIDIA

NVIDIA

Posted via Workday

Data Analytics CPU Workload Performance Product Manager

Posted Oct 16, 2026

Role at a glance

Job function
Product, Strategy & Operations Product Management & Product Ownership
Salary
Not yet verified Check the description for pay details; an amount or pay period has not been verified.
Location
Santa Clara, California, United States
Employment
Full-time
Experience
12+ years of experience in technical product management, performance engineering, or a closely related area.
Education
BS or MS in Computer Science, Electrical or Computer Engineering — or equivalent experience.

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Role Summary

AI-generated

The Data Analytics CPU Workload Performance Product Manager owns NVIDIA data center CPU workload and market strategy for data analytics and data processing. The role connects workload evidence and market positioning with roadmap decisions, CPU and platform requirements, and customer-facing proof points.

What You'll Do

  • Identify priority workloads, customer scenarios, benchmarks, and proof points to guide the roadmap.
  • Lead the lifecycle of benchmarks such as TPC-H and TPC-DS, including methodology, cluster and benchmarking architecture, competitive...
  • Translate disk, cache, memory, I/O, clustering, availability, and software behavior into CPU, platform, and system requirements, and...
  • Build quantitative value propositions across performance, infrastructure, software licensing, power, and total cost of ownership.
  • Work with external ISVs, database and analytics vendors, cloud providers, and strategic customers to validate requirements and develop...
  • Use benchmark results and customer evidence to inform product decisions, competitive responses, customer proof points, and field...

Generated from the employer's posting. Verify important details before applying.

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Qualifications

Requires 12+ years of experience in technical product management, performance engineering, or a closely related area, and a BS or MS in Computer Science, Electrical or Computer Engineering, or equivalent experience. Requires practical knowledge of CPU and database performance; understanding of system hardware characteristics affecting analytics performance, including caching, clustering, high availability, memory and I/O sensitivity, and architectural trade-offs; ability to translate workload performance into product, platform, and feature requirements; and experience collaborating with external ISVs, silicon vendors, or the broader analytics ecosystem.

Required

  • 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, including caching and clustering methods, high...
  • 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

  • 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.

Original job description

Content provided by the employer

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.


What you'll be doing:

  • 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.

What we need to see:

  • 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.

Ways to stand out from the crowd:

  • 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.

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.

NVIDIA

About the company

NVIDIA

Large Enterprise

NVIDIA is a leading technology company renowned for its graphics processing units (GPUs) and innovative computing solutions that enhance visual experiences across multiple platforms, including gaming, scientific research, and artificial intelligence. Founded in 1993, the company has expanded its offerings to include powerful AI frameworks and deep learning platforms, making significant contributions to industries such as gaming, data centers, automotive, and healthcare. NVIDIA's commitment to pushing the boundaries of visual computing continues to drive advancements in both hardware and software, positioning the company at the forefront of emerging technologies and digital transformation.