Join a team of engineers at NVIDIA dedicated to building the operational data foundation that powers reliability and resiliency across the DGX Cloud program. Our team designs and operates the data platforms, pipelines, and schemas that enable engineering and leadership teams to measure, understand, and improve operational excellence at scale. As the DGX Cloud program grows, enabling teams to develop, deploy, and manage accelerated computing infrastructure is a top priority, and this team sits at the center of that mission.
What you’ll be doing:
- Own and operate the data platform end to end, including the pipelines that ingest, transform, and serve operational data to leadership and partner teams.
- Ensure the reliability of those pipelines by setting and meeting targets for uptime, data freshness, and quality, and by leading incident response, root cause analysis, and prevention work.
- Define, instrument, and report on operational success metrics such as SLIs/SLOs, pipeline latency, and data completeness, and use them to drive prioritization and continuous improvement.
- Partner with customer teams to understand their data needs, translate those needs into platform capabilities and schemas, and set clear expectations for support and delivery.
- Provide technical leadership by setting engineering standards, reviewing designs and code, mentoring engineers, and driving the platform roadmap.
What we need to see:
- 7+ years of experience in software technical leadership roles in an agile software development environment.
- BS in Computer Science, Engineering, or a related field, or equivalent experience.
- Confirmed experience owning and operating production data pipelines, with a track record of keeping them reliable, observable, and fresh.
- Hands-on expertise in Databricks, including designing and leading schemas, tables, and access patterns using Delta Lake.
- Strong Python skills, with experience building maintainable, well-tested, production-grade data code.
- Solid understanding of medallion architecture and data modeling practices, with the judgment to apply them to balance data quality, performance, and usability.
- Experience applying data lineage, retention, and access policies in production environments.
Ways to stand out from the crowd:
- Experience building data products and tooling that enables agentic workflows and analysis.
- Experience working with APIs for operational data including PagerDuty, Rootly, and Backstage.
#LI-Hybrid
Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are:
184,000 USD – 287,500 USD for Level 4; and 224,000 USD – 356,500 USD for Level 5.
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
- 7+ years of experience in software technical leadership roles in an agile software development environment
- Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent experience
- Experience owning and operating production data pipelines with demonstrated reliability, observability, and freshness
- Hands-on expertise in Databricks, including designing schemas, tables, and access patterns using Delta Lake
- Strong Python skills and experience building maintainable, well-tested, production-grade data code
- Understanding of medallion architecture and data modeling practices
- Experience applying data lineage, retention, and access policies in production environments
- Experience building data products and tooling for agentic workflows and analysis
- Experience working with PagerDuty, Rootly, and Backstage APIs for operational data
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 — Feedback suggests equity grants, stock options/RSUs, and a discounted ESPP materially boost total compensation and can deliver significant wealth-building when the stock performs well.
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Healthcare Strength — Feedback suggests medical, dental, and vision plans with in-network preventive care at 100%, telehealth, and concierge-style support are comprehensive and valued.
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Parental & Family Support — Feedback suggests up to 22 weeks fully paid parental leave, fertility coverage, and adoption/surrogacy reimbursement provide strong family-focused benefits.
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.”
