Senior Engineer, DGX Cloud Resilience Engineering - Data Platform

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.

• →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.

• 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.

• 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

This posting is for an existing vacancy. 

NVIDIA uses AI tools in its recruiting processes.