Databricks
Staff Technical Program Manager- Security
$222K–$306K
Mountain View, California +2 · Staff · Full-time · Posted Oct 2, 2026
- Location
- Mountain View, California
San Francisco, California
San Francisco, California - Experience
- 8+ years.
- Education
- Bachelor’s degree in Computer Science, Computer Engineering, or equivalent technical experience.
About the job
Leads cross-functional security engineering programs to deliver scalable systems for identity integrity, data privacy, access control, and platform abuse prevention.
What you'll do
- Own security program strategy and roadmap, and drive initiatives across identity, governance, platform security, machine learning, and trust engineering.
- Coordinate complex, multi-team security initiatives from planning through delivery, resolving dependencies, risks, and roadblocks.
- Define security metrics and report program progress, risks, and impact to technical and executive audiences.
What they ask for
- Bachelor’s degree in Computer Science, Computer Engineering, or equivalent technical experience.
- 8+ years of progressive experience in technical program management, engineering program management, security program management, or an equivalent technical leadership role.
- Demonstrated ability to translate security, privacy, identity access, and trust engineering objectives into technical strategy, execution plans, and measurable outcomes.
- Experience using AI-enabled tools to accelerate program strategy, technical problem-solving, analysis, and automation.
Nice to have
- Experience in hyperscale cloud environments such as AWS, Azure, or GCP, or complex distributed data-processing environments.
- Prior hands-on software, systems, or security engineering experience before transitioning to Technical Program Management.
Pay
$222,500 — $305,900 USD (base salary)
Tools
OAuth 2.0, OIDC, AWS, Azure, GCP, IAM, PKI, Cryptography
AI focus
Uses AI-enabled tools to accelerate program strategy, technical problem-solving, analysis, and automation; the role also partners with Machine Learning teams on anomaly detection and abuse prevention systems.
Model-written summary · the original posting is authoritative