Principal Security Data Engineer, Infrastructure Security Engineering - DGX Cloud

Details

Role Overview

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

• Security Data Pipelines: Design, build, and operate ingestion and transformation pipelines that collect security telemetry and asset inventory from dozens of heterogeneous sources, and normalize them into one canonical model.
• Data Lake & Lakehouse Engineering: Architect and run the storage layer using open formats and schema flexibility to absorb structured inventory, semi-structured telemetry, and unstructured logs without constant, breaking migrations.
• Security Analytics & Detection Engineering: Build the query and analytics layer that powers posture scoring, coverage and drift metrics, freshness monitoring, and multi-source correlation.
• Securing the Data Layer Itself: 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 so that data freshness/coverage issues are detectable.
• Multi-Functional Collaboration: Partner with security control plane, inventory systems, identity and 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; building systemic solutions rather than manual data wrangling or "tool administration"; Bachelor’s degree or equivalent.
• Production-Grade Coding: Ability to write clean, maintainable, well-tested code (e.g., Python, Go, Scala, SQL) and comfortable building/operating production data services at scale.
• Data Modeling & Schema Design: Ability to design canonical schemas and data models that span many disparate sources and evolve over time without breaking consumers.
• Distributed Data Systems: Hands-on experience with modern data stacks, including streaming and batch processing, object storage, open table formats, and interactive query engines.
• Security-Minded Data Handling: Build defensible data systems with access control, encryption, audit, and isolation as first-class concerns; understanding security data sensitivity.
• Analytics Enablement: Track record of making large, messy datasets useful for interactive analysts, dashboards, and downstream services with data they can trust and query at low latency.
• Foundation: Bachelor’s degree in Computer Science, Engineering, or related technical field (or equivalent experience).

Ways To Stand Out from the Crowd

• Security Telemetry & Detection Engineering: Experience building SIEM or data-lake detection content; normalizing security logs into common schemas (e.g., OCSF, ECS); engineering the data layer that feeds correlation and anomaly-detection systems.
• Real-Time & Streaming Data: Expertise building low-latency, near-real-time pipelines where correlation is only as fast as the slowest input; detection measured in minutes.
• HPC/AI Fleet Telemetry: Experience working with GPU and hardware telemetry (DCGM, Redfish/BMC, InfiniBand) or fleet-scale observability across hundreds of thousands of devices.
• AI-Ready Data: Experience engineering data and feature layers that feed ML or LLM-based reasoning systems, enabling agents to correlate, predict, and act on trustworthy data.

Additional Information

• Base salary range: 272,000 USD - 431,250 USD (determined based on location, experience, and pay of employees in similar positions).
• Eligible for equity and benefits.
• Applications accepted at least until June 13, 2026.
• NVIDIA uses AI tools in its recruiting processes.