Senior Technical Program Manager, Data Platform

NVIDIA•Santa Clara, CA

1d•Hybrid

About The Position

Hardware Infrastructure is seeking a Senior Technical Program Manager to lead the strategy and evolution of our internal data platform ecosystem used across silicon development. This role will drive the platform’s expansion to deliver critical systems and services that support analytics, machine learning, and business intelligence. You’ll help define strategy, align stakeholders, and ensure execution at scale. This role sits at the intersection of hardware engineering, data, and infrastructure, driving programs that power scalable, reliable, and efficient data platforms. Hardware Infrastructure serves as the foundational platform for silicon development. We build and operate the systems, environments, and tools that enable hardware engineers to design, simulate, validate, and tape out chips. In addition, we support software teams specifically through our source control platforms, enabling development of new products. Our mission is to accelerate engineering velocity while maintaining the performance, efficiency, and reliability required to deliver world-class silicon, while ensuring seamless collaboration where hardware and software development intersect.

Requirements

B.S. (or equivalent experience) in Computer Science or a related technical field
12+ years of technical program management experience, including ownership in data infrastructure, distributed systems, or on-prem platforms at large scale (multi-TB/day)
Familiarity with data ecosystems (ex: ETL/ELT pipelines, data lakes/warehouses, etc) and technologies like Spark, Kafka, Airflow, Snowflake, or similar ecosystems
Strong understanding of system design concepts such as scalability, reliability, and performance
Demonstrated experience partnering with highly technical engineering teams and driving products from concept through delivery
Analytical approach, including defining success measures, tracking adoption, and finding opportunities to improve workflow efficiency
Excellent cross-functional leadership and communication skills, with the ability to influence without authority across multiple teams
Experience working in environments with geo-distributed teams and complex collaboration requirements
Track record of driving adoption of internal platforms and influencing engineering culture

Nice To Haves

Experience supporting hardware or silicon development environments, including pre-silicon development workflows
Background with working on modern data platforms (e.g., real-time streaming, large-scale batch processing) in on-prem or hybrid environments with infrastructure-as-code practices
Experience in data governance, privacy, or compliance initiatives
Experience supporting or scaling AI/ML platforms and infrastructure, with an understanding of the tooling, workflows, and operational requirements that ML teams need
Familiarity with FinOps principles and cloud cost optimization strategies, including resource tagging, rightsizing, and cost allocation frameworks to drive infrastructure efficiency at scale

Responsibilities

Own and drive end-to-end delivery of large-scale data infrastructure programs (ex: data lake, data platforms, pipelines, etc)
Partner with Hardware engineering and data engineering teams to define roadmaps, scope, and technical requirements
Translate ambiguous business needs into structured plans with clear milestones, risks, and dependencies
Manage cross-team coordination, program governance, status tracking, reporting, and stakeholder communication
Identify and mitigate risks, resolve blockers, and drive timely decisions across all initiatives
Improve operational efficiency by introducing scalable processes, tools, and best practices
Ensure reliability, scalability, performance, data quality, observability, and governance standards are embedded in all initiatives
Drive post-launch evaluations, retrospectives, and continuous improvement