NVIDIA logo
NVIDIA

NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you! Applications for this job will be accepted at least until June 15, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

Principal Security Data Engineer, Infrastructure Security Engineering

Security EngineerSecurity EngineerFull TimeRemoteLeadTeam 10,001+Since 1993H1B SponsorCompany SiteLinkedIn

Location

California

Posted

6 days ago

Salary

$272K - $431.3K / year

Seniority

Lead

Bachelor Degree15 yrs expExperience acceptedEnglishPythonScalaSQLGo

Job Description

Principal Security Data Engineer, Infrastructure Security Engineering

NVIDIA

• Design, build, and operate the ingestion and transformation pipelines for security telemetry • Architect the storage layer for a data lake/lakehouse • Build the query and analytics layer for security metrics • Engineer encryption at rest and in transit, fine-grained RBAC/ABAC, audit logging • Ensure data quality and trust by building for stable identity and source attribution • Collaborate with security teams to define data contracts early

Job Requirements

  • 15+ years of experience designing, building, and operating production data pipelines
  • Bachelor's degree or equivalent
  • Strong software engineering background with the ability to write clean, maintainable, and well-tested code (e.g., Python, Go, Scala, SQL)
  • Proven ability to design canonical schemas and data models that span many disparate sources
  • Hands-on experience with modern data stacks, both streaming and batch processing
  • Understanding of access control, encryption, audit, and isolation in data systems
  • A track record of making large, messy datasets genuinely useful

Benefits

  • equity
  • benefits

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