Principal Security Data Engineer, Infrastructure Security Engineering - DGX Cloud

Details

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 ingestion and transformation pipelines that collect security telemetry and asset inventory from dozens of heterogeneous sources and normalize them into a canonical model.
• Architect and run the storage layer (data lake / lakehouse) built on open formats with schema flexibility for structured inventory, semi-structured telemetry, and unstructured logs.
• Build the query and analytics layer that powers posture scoring, coverage and drift metrics, freshness monitoring, and multi-source correlation.
• Engineer security controls for the data layer: encryption at rest and in transit, fine-grained RBAC/ABAC, non-repudiable audit logging, data classification, network isolation, and verifiable retention and purge.
• Ensure data quality and trust: stable identity, source attribution, append-only history, and mechanisms to detect when a source goes quiet.
• Collaborate with security control plane, inventory, identity, endpoint teams, and broader NVIDIA data and security organizations to define data contracts early.

Requirements

• Data engineering at scale: 15+ years of experience designing, building, and operating production data pipelines, lakes, or lakehouses at high volume and throughput. Focus on systemic solutions rather than manual data wrangling. Bachelor’s degree or equivalent.
• Production-grade coding: strong software engineering background; ability to write clean, maintainable, well-tested code (examples called out: Python, Go, Scala, SQL). Comfortable building and operating production data services at scale.
• Data modeling & schema design: experience designing canonical schemas and data models that span many disparate sources and evolve without breaking consumers.
• Distributed data systems: hands-on experience with modern data stacks, both streaming and batch processing, object storage, open table formats, and interactive query engines.
• Security-minded data handling: design data systems with defensibility in mind (access control, encryption, audit, isolation); understanding that security data is highly sensitive.
• Analytics enablement: track record of making large, messy datasets useful for interactive analysts, dashboards, and downstream services with low-latency queryability.
• Foundation: Bachelor’s degree in Computer Science, Engineering, or a related technical field (or equivalent experience).

Ways To Stand Out

• Experience building SIEM or data-lake detection content, normalizing security logs into common schemas (e.g., OCSF, ECS), or engineering the data layer for correlation and anomaly-detection systems.
• Expertise building low-latency, near-real-time pipelines for fast correlation and detection.
• Experience with HPC/AI fleet telemetry and GPU or hardware telemetry (examples cited: DCGM, Redfish/BMC, InfiniBand) or fleet-scale observability across hundreds of thousands of devices.
• Experience engineering AI-ready data and feature layers that feed ML or LLM-based reasoning systems while making that data safe to reason over.

Compensation & Additional Information

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 272,000 USD - 431,250 USD.

You will also be eligible for equity and benefits. Applications for this job will be accepted at least until June 13, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes and is an equal opportunity employer.