Senior Data Application Engineer – Enterprise Data ManagementSan Francisco

NVIDIA · US, CA, Santa Clara

Posted Posted 50 mins ago
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This Senior Data Application Engineer – Enterprise Data Management role at NVIDIA was posted in the last 5 days. Before applying, run your resume through the checker on the right — most rejections here are keyword and formatting mismatches, not qualifications.

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent. As an NVIDIAN, you'll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Join our team and discover how you can build a lasting impact on the world. We are seeking a highly motivated and experienced Senior Data Application Engineer, to join our Enterprise Data Management team. This is a role at the intersection of product strategy, data observability and AI enablement. You will define the product vision and architecture for NVIDIA's data integrity and observability capabilities. You will develop reusable frameworks deployable across business functions. You will also partner with senior EDM architects and business collaborators to scale trusted data across the enterprise. What You'll Be Doing: • Product Roadmap -  Drive the end-to-end product vision for data observability — defining what gets built, in what order, and why. Engage directly with business partners to surface areas of highest impact, translate difficulties into a prioritized roadmap, and maintain alignment with business from inception through execution. • Architecture and Framework - Design the architecture for EDM data observability platform with reusability as a first principle. Identify common data quality and integrity challenges across supply chain processes and build modular, configurable solutions that eliminate one-off implementations and accelerate onboarding of new business domains. • Agentic Frameworks - Design and deliver AI-powered observability capabilities by building and operationalizing enterprise-grade agentic frameworks — encompassing orchestration layers, tool-use patterns, and feedback loops — that enable self-healing data pipelines, automated anomaly detection and triage, and proactive surfacing of data integrity issues before they impact operations. • Delivery - Take full ownership from requirements through deployment — defining what gets monitored, how alerts are ranked by business impact, and how blocking issues are tracked and resolved. Drive accountability across engineering, data, and business teams to ensure data observability solutions are delivered on time and adopted at scale. • Supply Chain Experience - Ground every observability decision in a deep understanding of Hitech supply chain business processes —planning, procurement, manufacturing, operations, finance, sales  — to ensure solutions address root causes, not symptoms. Build the data specifications, business glossaries, governance rules, and lineage maps that make observability meaningful and enterprise AI data agents trustworthy in production. • Design and build foundational data infrastructure powering EDM’s data observability ecosystem. Large language model inferencing is the core engine for all observability and agentic capabilities. Design the inferencing stack — including model selection, prompt engineering standards, context window management, and output validation pipelines — ensuring LLMs are deployed in a way that is accurate, governed, and fit for enterprise use cases. • Data Governance Foundation – Partner with EDM architects and business to define the enterprise data governance artifacts that ensure both observability and AI reliability — including data assets, business glossaries, data quality rules, ownership, and process flows. Drive adoption of data ownership models that assign clear accountability for data quality at the domain level, so that issues surfaced by observability frameworks have a clear owner and resolution path. • AI-Led SDLC. Champion AI-assisted software development methodologies to drive high-quality, fast-paced delivery across the observability product portfolio What We Need to See: • 10+ years of experience in Data & product management, with a track record of deploying enterprise-grade AI or data solutions at scale in a complex enterprise environment. • Experience building and owning knowledge frameworks for AI agent deployment, including data specifications, business glossaries, governance policies, lineage and process flows. • Working knowledge of enterprise data platforms: Databricks (Delta Lake, PySpark), Palantir, Informatica and ETL/ELT tools & pipeline patterns. • Familiarity with agentic AI workflows (LLM-based agents, RAG, orchestration frameworks) and experience deploying them in production for data quality, self-healing, or observability use cases. • Strong foundation in master data management , data quality and governance with experience integrating data platforms with ERP solutions, data lakes, enterprise applications and document repositories • Demonstrated ability to build senior stakeholder relationships across business, IT, and operations, including presenting complex technical concepts to non-technical audiences. • Working knowledge of supply chain and manufacturing data domains: Material Master, BOM, Supplier Data, Reference Data, and how they flow across planning and execution systems. • Experience in deploying software using CI/CD tools such as Jira, Jenkins, Git etc. • Full stack experience preferred with strong knowledge of sql, python, pyspark and working knowledge of React, Angular, NodeJs. • Bachelor's or Master's degree in Computer Science, Data Engineering, or equivalent experience in enterprise data architecture and product management. NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative, results-oriented and enjoy having fun, then what are you waiting for? Apply today! Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 168,000 USD - 264,500 USD for Level 4, and 196,000 USD - 310,500 USD for Level 5. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until September 27, 2026. 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.

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