Senior Data Observability & AI Platform Engineer

NVIDIA; Santa Clara (CA); On-site; USD 168,000 - 311,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA is seeking a Senior Data Application Engineer to join the Enterprise Data Management team in Santa Clara. You will define the product vision and architecture for data integrity and observability, building reusable frameworks and partnering with EDM architects to scale trusted data across the enterprise.

You'll own end-to-end delivery, design AI-powered observability, and work across supply chain domains to ensure data quality, governance, and production readiness.

Qualifications

• 10+ years in data and product management in enterprise settings.
• Experience building AI agent deployment frameworks and governance.
• Knowledge of data platforms like Databricks, Palantir, and Informatica.
• Familiarity with CI/CD tools and data quality processes.
• Strong data governance, lineage, and stakeholder collaboration.

Responsibilities

• Define product vision and architecture for data integrity and observability.
• Develop reusable frameworks across business functions.
• Partner with EDM architects to scale trusted data enterprise-wide.
• Own delivery from requirements to deployment and adoption at scale.
• Design AI-powered observability capabilities and agentic workflows.
• Lead governance artifacts: glossaries, rules, and ownership.

Skills

Data & product management

AI agent deployment

Stakeholder management

Enterprise data governance

Data platform knowledge

Education

CS/Data Eng degree

Tools

Databricks

Palantir

Informatica

ETL/ELT

Jira

Jenkins

Git

PySpark

SQL

React/Angular/NodeJs

Job description

NVIDIA is seeking a Senior Data Application Engineer to join the Enterprise Data Management team in Santa Clara. You will define the product vision and architecture for data integrity and observability, building reusable frameworks and partnering with EDM architects to scale trusted data across the enterprise.

You'll own end-to-end delivery, design AI-powered observability, and work across supply chain domains to ensure data quality, governance, and production readiness.