Director, Engineering Governance- Mountain View, CA
Databricks is seeking a Director of Engineering Governance to lead the integration of security, privacy, and responsible data practices into the core of its products and infrastructure. This strategic role involves designing and scaling engineering platforms, guardrails, and operating models to ensure secure and compliant product development across a rapidly growing, multi-cloud ecosystem. The position is based in Mountain View, CA, and offers a unique opportunity to influence the foundational governance systems that enable Databricks to innovate swiftly while maintaining world-class security and customer trust.
In this role, the Director will define the company-wide strategy for embedding security, privacy, and responsible data use across engineering workflows and platform components. They will build scalable governance frameworks that assist engineering teams in designing secure systems from the outset. Additionally, the Director will establish and lead a Security & Privacy Postmortem Review process to drive learning, accountability, and long-term resilience, ensuring that insights from incidents translate into systemic improvements across tools, infrastructure, and engineering culture. They will also rebuild and scale a Security Champions Network to integrate security and governance expertise directly into product and infrastructure teams, creating centralized enablement, tooling, and shared learning systems that allow thousands of engineers to integrate security seamlessly. Furthermore, the Director will lead efforts to ensure responsible data use across AI/ML systems, SaaS environments, and internal workspaces, defining and enforcing policies that uphold privacy, integrity, auditability, and proper data lifecycle management. They will transform security into a key enabler for engineering velocity by delivering automation, self-service tools, and intelligent guardrails that reduce developer friction while increasing safety and compliance. Finally, the Director will identify and elevate Databricks' security posture to exceed customer expectations, including areas such as audit logging, controlled access workflows, secure asset import/export, and behavior monitoring and lineage, partnering with security, IT, and compliance teams to ensure readiness for the most demanding enterprise and regulated environments.
The ideal candidate will have over 10 years of experience in large-scale software engineering, with several years leading engineering managers and senior individual contributors. A strong technical grounding in backend systems, distributed systems, identity/security, or enterprise cloud platforms is essential. Experience defining governance, security, or enterprise-grade platform capabilities is required, along with a background as a senior individual contributor (e.g., Staff/Principal Engineer) to ensure deep technical credibility. Proven success in hiring, developing, and retaining senior engineering talent is necessary, as is expertise in driving cross-functional technical programs with senior stakeholders. Preferred qualifications include experience building cloud-agnostic or multi-cloud services, a background in enterprise features such as access control, policy engines, compliance, or identity systems, and experience leading organizations through scaling phases in high-growth environments.
The compensation for this role includes a base salary ranging from $255,900 to $305,350 USD per year, with additional benefits such as an annual performance bonus and equity. Databricks offers comprehensive benefits and perks that meet the needs of all employees, including health and wellness programs, retirement plans, and professional development opportunities.
Databricks is committed to fostering a diverse and inclusive culture where everyone can excel. The company offers opportunities for growth and advancement, encouraging employees to take on new challenges and develop their skills. Joining Databricks means becoming part of a team that is dedicated to solving the world's toughest problems through data and AI, with a focus on innovation, collaboration, and customer success.