Senior Data Platform Engineer | Equity Eligible

NVIDIA; California (MO); On-site; USD 200,000 - 322,000; Full time

Job summary

NVIDIA is seeking a Senior Data Platform Engineer for the DGX Cloud Data Platform. You will own and guide the architecture for domain-scale data products, ingest pipelines, and telemetry processing to support engineering, operations, finance, and security teams.

You will lead cross-team initiatives, write essential code, and ensure secure production deployments, with a focus on reliability, performance, and cost optimization across multi-environment fleets.

Qualifications

• 12+ years of relevant industry experience with a Bachelor’s or equivalent experience, and a Master’s degree or equivalent experience in Computer Science, Engineering, or a related field.
• Hands-on ownership of production software, data platforms, databases, or distributed systems.
• Experience with distributed processing, analytical or relational databases, production ETL, streaming, or backend/cloud systems handling large data volumes.
• Strong software engineering fundamentals and production proficiency in a backend or systems language, with data-processing framework experience.

Responsibilities

• Define and guide the technical vision for a DGX Cloud Data Platform domain, incl. architecture and growth.
• Lead cross-team initiatives; translate requirements into architectures and interfaces; contribute code.
• Architect, implement, and evolve batch and streaming systems for fleet telemetry and cost data.

Skills

Distributed systems

Backend development

Data platforms

Cloud systems

SQL

Education

Bachelor’s degree or equivalent

Master’s degree or equivalent

Tools

SQL

CI/CD

ETL

Job description

NVIDIA is seeking a Senior Data Platform Engineer for the DGX Cloud Data Platform. You will own and guide the architecture for domain-scale data products, ingest pipelines, and telemetry processing to support engineering, operations, finance, and security teams.

You will lead cross-team initiatives, write essential code, and ensure secure production deployments, with a focus on reliability, performance, and cost optimization across multi-environment fleets.