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.
We are looking for a Senior Product Manager to define and own the DGX Cloud Data Platform and Analytics System! This platform is a governed data platform that brings together fleet and machine data from across DGX Cloud and publishes it as authoritative, joinable, fully traceable data products. The role owns the roadmap across the platform's crawl, walk, and run phases, defines the data products that let any team answer a cross-fleet question with a single query, and negotiates versioned data contracts with the teams that produce the data. It works in close partnership with engineering leadership, infrastructure security, and compliance to establish how aggregated fleet data is classified, accessed, retained, and audited. This is a foundational role on a new team, with a broad charter and highly visible outcomes.
What you'll be doing:
- Define requirements and acceptance criteria for the platform's flagship products: single-source-of-truth tables for clusters, associated components, customers, and workloads, along with the relationship tables that connect them
- Partner with source and collector teams across DGX Cloud to onboard their data and define versioned data contracts covering schema, semantics, freshness, quality, and change notification
- Drive identifier and schema standardization upstream with producing teams, so that every standardization decision is recorded, owned, and tracked to closure
- Work with infrastructure security, compliance, and enterprise data teams to define the security model
- Engage with engineering leadership to establish priorities and resource allocation, sequence delivery against firm external constraints, and gain prioritization consensus across many collaborating teams
- Define and report the measures that show the platform is working, including standardization debt per source, pipeline freshness and quality SLOs, source onboarding throughput, and time to first answer for a new consumer
- Define the requirements and build the case for extending the platform to NVIDIA Cloud Partners and cloud service providers.
What we need to see:
- 12+ years of total experience in technology, with product management or engineering experience in data platforms, cloud infrastructure, or AI/ML
- BS or MS in engineering, computer science, or another technical field (or equivalent experience)
- Demonstrated experience in definition of data platform, data infrastructure, or analytics product through multiple delivery phases, from first ingestion through to production consumers
- A solid background in data architecture, including layered or data contracts, schema and lineage management, data catalogues, and SQL as a primary consumer interface
- Working knowledge of data governance and access control concepts, including attribute-based access control, data classification, least privilege, retention, and audit evidence
- Demonstrated experience driving standardization and adoption across teams
- Ability to lead discussions, coordinate among diverse collaborators, and act as a trusted advisor
Ways to stand out from the crowd:
- Experience building single-source-of-truth entity models, CMDB, or inventory systems that reconcile identifiers across multiple source systems
- Familiarity with bi-temporal or append-only data modeling and point-in-time historical reconstruction
- Experience delivering data products consumed by AI agents through MCP, retrieval, or graph-backed context, as well as by human analysts
- Background in large-scale GPU, HPC, or data center fleet operations, observability, resource planning, or infrastructure security
- Experience productizing an internal platform for external partners, including disconnects
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 www.nvidiabenefits.com/
#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 208,000 USD - 327,750 USD.You will also be eligible for equity and benefits.
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.Skills Required
- 12+ years of total technology experience, including product management or engineering experience in data platforms, cloud infrastructure, or AI/ML
- BS or MS in engineering, computer science, or another technical field, or equivalent experience
- Experience defining data platform, data infrastructure, or analytics products through multiple delivery phases, from initial ingestion through production consumers
- Background in data architecture, including layered data contracts, schema and lineage management, data catalogues, and SQL as a primary consumer interface
- Working knowledge of data governance and access control, including attribute-based access control, data classification, least privilege, retention, and audit evidence
- Experience driving standardization and adoption across teams
- Ability to lead discussions, coordinate diverse collaborators, and act as a trusted advisor
- Experience building single-source-of-truth entity models, CMDB, or inventory systems that reconcile identifiers across multiple source systems
- Familiarity with bi-temporal or append-only data modeling and point-in-time historical reconstruction
- Experience delivering data products consumed by AI agents through MCP, retrieval, or graph-backed context, as well as by human analysts
- Background in large-scale GPU, HPC, or data center fleet operations, observability, resource planning, or infrastructure security
- Experience productizing an internal platform for external partners, including cloud service providers
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
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Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
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Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
NVIDIA Insights
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”



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