Senior Data Engineer

NVIDIA is hiring a Senior Data Engineer to join the Software Architecture Team. In this role, you will play a critical leadership position in driving data‑driven decision‑making and shaping the next generation of Data Center monitoring, analytics, and management platforms across NVIDIA. You will own and evolve large‑scale telemetry and analytics pipelines end‑to‑end, with a strong emphasis on data quality, scalability, and architectural excellence.

What You'll Be Doing

• Act as the technical owner and primary point of contact for ML/AI data pipelines, large‑scale data ingestion, and enterprise data warehousing.
• Lead the design and onboarding of new, high‑volume data sources to continuously expand and mature the centralized Data Lake.
• Partner with multiple NVIDIA product and infrastructure teams to translate complex business and technical requirements into scalable data solutions.
• Work closely with system architects, platform engineers, and data scientists to co‑design end‑to‑end analytics and ML‑ready architectures.
• Design, build, and optimize high‑performance ETL pipelines with strong guarantees around data integrity, reliability, and observability.
• Contribute to and influence the architecture of next‑generation monitoring, telemetry, and analytics platforms for hyperscale Data Centers.
• Provide technical leadership and mentorship, guiding teams toward best practices in data engineering and data‑driven decision‑making.
  
  

• BSc. or MSc. in Computer Science, Computer Engineering, or a related field.
• 5+ years of hands‑on experience in Data Engineering, large‑scale telemetry systems, and big‑data platforms.
• Deep understanding of telemetry architectures, automation technologies, and modern application platforms and paradigms.
• Strong familiarity with networking fundamentals; experience in data‑center environments is a strong advantage.
• Proven experience with modern analytics and big‑data platforms such as Spark, Databricks, and similar ecosystems.
• Solid understanding of different telemetry pipeline models and trade‑offs (streaming vs. batch, push vs. pull, real‑time vs. near‑real‑time).
• Advanced programming skills and a track record of building production‑grade data pipelines, tooling, and proof‑of‑concepts.
  
  

• Demonstrated ability to prototype complex ideas quickly and clearly articulate their business and technical value.
• Experience with cloud‑native development, deployment, and operational best practices.
• Hands‑on experience with public cloud platforms (AWS, GCP, Azure).
• Background in large‑scale data center architecture and infrastructure technologies.
• Contributions to open‑source projects or active participation in the data engineering community.