Staff Enterprise Security Engineer
Databricks is a data and AI platform that lets organizations build analytics, AI agents, and applications on a unified, governed lakehouse.
Funding history
Investors
About Databricks
Data engineers, analysts, and AI teams use Databricks to process large datasets, build reliable pipelines, and train models on a single governed platform. Users can run SQL analytics, serve ML predictions in real time, and deploy AI agents grounded in enterprise data. Its open lakehouse architecture provides consistent security and governance across analytical and operational workloads.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will expand Enterprise Security coverage across enterprise applications, integrations, data flows and AI-adjacent use cases. You will review implementation designs with the Data team for work on the Databricks platform, assess new technologies for secure design, define practical security requirements, and build automation and security AI agents that scale coverage.
Requirements
- 8+ years in security engineering, enterprise, application or cloud security
- Experience conducting security design or architecture reviews
- Hands-on familiarity with Databricks or comparable data/AI platforms (Unity Catalog, service principals)
- Strong understanding of authentication, authorization, SSO, federation, SCIM, API security, token handling, secrets management
- Experience assessing data flows, integrations, trust boundaries, logging and monitoring
- Proven track record building security automation in production (Python, SQL, Terraform)
- Ability to evaluate risk in automation platforms and AI-adjacent workflows such as MCP
- Strong written and verbal communication
- Familiarity with cloud platforms, identity systems, audit logging, encryption, access control, incident response
Responsibilities
- Establish an engagement model with the Data team for security review of designs, hardening and tracked remediation
- Conduct security design reviews of enterprise applications, SaaS platforms and integrations
- Assess data flows, third-party integrations, trust boundaries and AI-adjacent workflows including MCP
- Partner with Product Engineering, IT, Legal Privacy and business stakeholders to surface risk early
- Define clear security requirements and guidance
- Build automation and agent capabilities including SSPM-style controls and Security AI Personas
Benefits
- Eligibility for annual performance bonus
- Equity