principal Data Engineer tech_leadership 15+ yrs Bachelor's · Posted Apr 20, 2026

About this role

Nvidia is hiring a principal-level Data Engineer based in Santa Clara, CA. The posting calls out experience with Observability, Python, JavaScript, Java and roughly 15+ years of relevant work. Listed education preference: a bachelor's degree or equivalent.

Role
Data Engineer
Function
data engineering
Level
principal
Track
Tech leadership
Employment
Full-time
Location
Santa Clara, CA
Experience
15+ years
Education
Bachelor's degree
Posted
Apr 20, 2026
AI Summary
Principal Data Platform Architect leading design and implementation of distributed observability systems for AI/HPC clusters. Architect data collection, pipelines, and visualization services while collaborating with engineering teams. Requires 15+ years experience with large-scale distributed systems, Python/Java expertise, and database knowledge.

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Job description

from Nvidia careers

NVIDIA’s Hardware Infrastructure organization is seeking a Principal Data Platform Architect. We serve and collaborate directly with NVIDIA’s rapidly growing AI, HW, and SW engineering and research teams across the company. We are looking for a technical leader to define a vision and roadmap for distributed data platform and observability systems for large-scale AI and HPC clusters and workloads and guide implementation towards this vision. You will architect systems for data collection, aggregation, enrichment, storage, retrieval, and visualization to spectacularly improve efficiency, performance, and productivity of AI and HPC workloads. You will lead technical teams to develop, deploy, and operate observability solutions for multiple compute clusters around the world.

What You’ll Be Doing:

  • Collaborate with AI, HW, and SW engineering and research teams to define a vision and roadmap for AI/HPC cluster observability.

  • Architect and lead teams to develop, test, and deploy data collectors, pipelines, visualization and retrieval services.

  • Define data collection and retention polices to balance network bandwidth, system load, and storage capacity costs with data analysis requirements.

  • Work in a diverse team to provide operational and strategic data to empower our engineers and researchers to improve performance, productivity, and efficiency.

  • Continuously improve quality, workloads, and processes through better observability.

    This is an excerpt. Read the full job description on Nvidia careers →
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