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Databricks

Builds cloud software for data analysis and AI

Staff Technical Program Manager-Security

Program ManagementConfirmed live in the last 24 hours
Full-time

About the Job

Requirements

  • Proven experience leading large-scale, ambiguous security programs across organizational boundaries, ideally in cloud-native or SaaS environments.
  • Strong strategic thinking and ability to translate vision into execution and align senior stakeholders.
  • Deep technical literacy in identity and access management (OAuth 2.0/OpenID Connect), data privacy controls, anomaly detection pipelines, abuse prevention systems, and risk assessment.
  • Ability to develop scalable solutions, optimize processes, and foster a security-by-default mindset across engineering and developer teams.
  • Data-driven approach to defining metrics, surfacing insights, and using results to shape strategy and demonstrate impact.
  • 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.
  • Ability to translate data privacy, identity access, and trust engineering requirements and objectives into technical strategy, architecture decisions, execution plans, and measurable outcomes.
  • Ability to resolve conflicting priorities and resource constraints across cross-functional teams without direct authority, establish organization-wide engineering processes, and deliver complex, multi-team roadmaps.
  • Strong written and verbal communication skills, including presenting complex technical strategies to executive engineering leaders.
  • Experience using AI-enabled tools to accelerate program strategy, technical problem-solving, analysis, and automation.
  • Ability to work onsite three days per week in Bellevue, Seattle, San Francisco, or Mountain View.

Responsibilities

  • Define, articulate, and own the security program strategy and roadmap, ensuring alignment with business and product goals.
  • Drive initiatives across Identity Infrastructure, Data Governance, Platform Security, Machine Learning, and Trust Engineering.
  • Oversee execution of complex security engineering multi-half initiatives (authentication, authorization, secrets, public key infrastructure, and cryptography), owning delivery from strategy through outcomes.
  • Use technical knowledge of cloud, distributed systems, and security engineering to influence design decisions, identify risks, and remove roadblocks.
  • Define and track security metrics (KPIs and OKRs), using data to drive decisions, communicate program health, and measure business impact.
  • Present program status, risks, and progress to executive and technical audiences, building trust and ensuring transparency around security posture.
  • Work directly with Security Engineering, Identity Infrastructure, Machine Learning, and Core Platform teams to design, build, and deploy systems for authentication, access control, and anomaly detection.
  • Translate identity protocols, privacy-by-design principles, and threat mitigation models into technical specifications, system dependencies, and actionable execution roadmaps.

Desired Qualifications

  • Experience operating in hyperscale cloud environments such as AWS, Azure, or Google Cloud Platform, or in complex distributed data-processing environments.
  • Prior hands-on experience as a software, systems, or security engineer before transitioning to Technical Program Management.
  • Familiarity with unified data governance architectures, distributed-systems security, and security controls supporting AI and machine-learning infrastructure.

About the Company

Databricks

Builds cloud software for data analysis and AI

Databricks builds cloud software that businesses use to organize data, analyze it, and develop AI applications. Its lakehouse architecture brings the flexible storage of a data lake together with the querying and management tools of a data warehouse. Data engineers prepare and update datasets, analysts build reports, and developers train models or create applications in a shared workspace with controls over who can use the data. The platform runs on Amazon, Microsoft, and Google clouds, and customers pay for computing usage or commit to longer contracts for discounted rates. Databricks was founded in 2013 and is headquartered in San Francisco, California.

Company size
10,001+
Company stage
Late Stage VC
Total funding
$32.1B
Headquarters
San Francisco, CA
Founded
2013

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