Security Data Engineer

NVIDIA NVIDIA · Semiconductors · CA +1 · Remote

This role focuses on building and operating the data platform that powers security operations across NVIDIA, transforming raw security telemetry into usable intelligence for detection, automation, and AI-driven security operations.

What you'd actually do

  1. Design and operate telemetry ingestion pipelines that collect and process data from endpoint, identity, network, cloud, and other enterprise security sources.
  2. Normalize and enrich telemetry into structured datasets using standardized schemas and entity models so signals from different systems can be correlated consistently.
  3. Build and maintain data models and graph ready structures that connect users, devices, identities, and activity across the security ecosystem.
  4. Provide governed access to security datasets through APIs, query interfaces, and streaming pipelines used by Detection, Automation, AI, and Analytics teams.
  5. Define lifecycle and retention strategies across hot, cold, and archive storage tiers to balance performance, scalability, and cost.

Skills

Required

  • Bachelor’s degree in Computer Science, Engineering, Cybersecurity, Data Engineering, or a related technical field, or equivalent experience.
  • 5+ years of experience designing and operating large scale data pipelines in a security or enterprise data environment.
  • Strong understanding of security telemetry including endpoint, identity, network, cloud, and email data sources.
  • Experience working with modern data platforms and ingestion technologies such as Databricks, Snowflake, Kafka, Spark, Flink, or similar systems.
  • Hands on experience with data normalization frameworks or standards such as OCSF, ECS, or equivalent approaches.
  • Understanding of data access patterns including APIs, query interfaces, and role based access control.
  • Ability to collaborate across teams and clearly document complex data systems for a broad technical audience.

Nice to have

  • Experience working with security platforms such as CrowdStrike NG SIEM, Splunk, or Microsoft Sentinel.
  • Familiarity with SIEM data models, detection engineering workflows, and SOAR integrations.
  • Experience with graph databases or entity relationship modeling for security data.

What the JD emphasized

  • security data platform
  • security telemetry
  • data normalization frameworks or standards such as OCSF, ECS, or equivalent approaches