Principal Security Data Engineer, Infrastructure Security Engineering - DGX Cloud
About the role
NVIDIA DGX Cloud is the AI supercomputing-as-a-service substrate designed to power the next generation of AI and industrial-scale breakthroughs. As a Security Data Engineer within our Infrastructure Security Engineering organization, you will build the data backbone of our security control plane—the pipelines, lake, and analytics that turn fragmented telemetry from a 250,000+ GPU fleet into a single, queryable, trustworthy picture of security state.
Responsibilities
Design, build, and operate the ingestion and transformation pipelines that collect security telemetry and asset inventory from dozens of heterogeneous sources, and normalize them into one canonical model.
Architect and run the storage layer. A data lake/lakehouse built on open formats, with the schema flexibility to absorb structured inventory, semi-structured telemetry, and unstructured logs without constant, breaking migrations.
Build the query and analytics layer that powers posture scoring, coverage and drift metrics, freshness monitoring, and multi-source correlation.
Secure the data layer itself. Treat the data platform as a high-value target, because it is. The data you store is a map of every host, every gap, and every credential path. You will engineer encryption at rest and in transit, fine-grained RBAC/ABAC, non-repudiable audit logging, data classification, network isolation, and verifiable retention and purge.
Data Quality & Trust: Build for stable identity, source attribution, append-only history, and honest coverage. Make a source going quiet a finding, not silence, so that every downstream number comes with a known confidence.
Multi-Functional Collaboration: Partner with the security control plane team, the inventory systems, identity and endpoint teams, and broader NVIDIA data and security organizations to define data contracts early, so these systems converge by design.
Requirements
Data Engineering at Scale: 15+ years of experience designing, building, and operating production data pipelines, lakes, or lakehouses at high volume and throughput. You build systemic solutions rather than performing manual data wrangling or "tool administration."
Production-Grade Coding: A strong software engineering background with the ability to write clean, maintainable, and well-tested code (e.g., Python, Go, Scala, SQL).
Data Modeling & Schema Design: Proven ability to design canonical schemas and data models that span many disparate sources and evolve over time without breaking the consumers that depend on them.
Distributed Data Systems: Hands-on experience with the modern data stacks, both streaming and batch processing, object storage, open table formats, and interactive query engines.
Security-Minded Data Handling: You design data systems that are themselves defensible. Access control, encryption, audit, and isolation are first-class concerns in your work, and you understand that security data is among the most sensitive data an organization holds.
Analytics Enablement: A track record of making large, messy datasets genuinely useful—serving interactive analysts, dashboards, and downstream services with data they can trust and query at low latency.
Qualifications
Foundation: Bachelor's degree in Computer Science, Engineering, or a related technical field (or equivalent experience).
Skills
Data Engineering at Scale
Production-Grade Coding
Data Modeling & Schema Design
Distributed Data Systems
Security-Minded Data Handling
Analytics Enablement
Benefits
Base salary range: 272,000 USD - 431,250 USD. Eligible for equity and benefits.
Pay
Base salary will be determined based on your location, experience, and the pay of employees in similar positions.
Schedule
Applications for this job will be accepted at least until June 13, 2026.