While candidates in the listed location(s) are encouraged for this role, candidates in other locations (US based) will be considered.
Mission
Databricks is hiring an L6 Staff Enterprise Security Engineer to expand Enterprise Security coverage across a rapidly evolving enterprise and product environment. This role will focus on securing enterprise applications, cross-system integrations, data flows, and emerging AI-adjacent use cases. The scope includes partnership with the Data team on corporate production development within the Databricks platform, through security reviews of implementation designs, hardening, configuration oversight, and broader enterprise data-security discussions, as well as modern access patterns such as MCP, integration, and trust boundary security, security automation, and broader security engineering support across enterprise platforms and services. This engineer will help identify risk, define practical security requirements, and improve security outcomes through strong technical judgment, hands-on engineering, and cross-functional partnership.
Opportunity
This role sits at the intersection of enterprise architecture, security engineering, product security partnership, and business enablement. Corporate production development within the Databricks platform remains owned by the Data team; EntSec defines how we engage, reviewing implementation designs, configurations, and data flows as capabilities are built, alongside ongoing enterprise application and integration reviews. The engineer will assess new technologies, integrations, and workflows with an emphasis on secure design, authentication and authorization, data handling, logging, third-party connectivity, API and token security, and operational resilience. The role partners closely with Product Engineering, IT, Legal Privacy, and business stakeholders to surface risk early, set clear requirements, and build automation that scales security coverage. This is a strong opportunity to help shape how Enterprise Security supports Databricks product development, enterprise data security, SaaS, and internal platforms, automation, and AI-connected systems as the environment continues to grow in complexity.
Requirements
8+ years of experience in security engineering, enterprise security, application security, cloud security, or a related field.
Experience conducting security design or architecture reviews for product features, enterprise applications, SaaS platforms, integrations, or internally developed systems.
Hands-on familiarity with the Databricks platform or comparable data/AI platforms (Unity Catalog, workspace governance, service principals, data access patterns).
Strong understanding of authentication, authorization, SSO, federation, SCIM, API security, token handling, secrets management, and least privilege design.
Experience assessing data flows, third-party integrations, trust boundaries, logging and monitoring, and security controls across interconnected systems.
Proven track record building security automation in production: monitoring, posture checks, review workflows, or tooling (Python, SQL, Terraform, or similar).
Ability to evaluate risk in modern enterprise environments, including automation platforms, AI-adjacent workflows, and emerging integration patterns such as MCP.
Strong written and verbal communication skills, including the ability to translate technical risk into clear requirements and actionable guidance.
Experience driving security outcomes through engineering judgment, influence, and scalable process improvement.
Familiarity with cloud platforms, enterprise identity systems, and core control domains such as audit logging, encryption, access control, data retention, and incident response.
Outcomes
OUTCOME 1: Establish a consistent EntSec engagement model with the Data team on corporate production development within the Databricks platform: security review of implementation designs, hardening guidance, configuration oversight, and tracked remediation, while Data retains ownership of product development and delivery.
OUTCOME 2: Strengthen security practices across enterprise applications, integration, and data-security reviews by identifying key risks early, improving requirement quality, and helping teams address security issues earlier in the lifecycle, including AI-adjacent workflows, data flows, and integration patterns.
OUTCOME 3: Build automation and agent capabilities, including SSPM-style controls and Security AI Personas, that help secure systems from the start, reduce dependency on manual review, and embed security guidance earlier in product and integration lifecycles.
Competencies
COMPETENCY 1: Product and Design Security Partnership. Partners effectively with product and engineering teams to review implementation designs, surface risk early, and drive practical security requirements without owning product delivery.
COMPETENCY 2: Data Security and Technical Judgment. Applies strong security judgment to data flows, platform configurations, access patterns, and enterprise data-security decisions on and across the Databricks platform.
COMPETENCY 3: Security Automation and Scalable Engineering. Builds durable automation, monitoring, and tooling that scales EntSec coverage and reduces repeated manual work.
Pay Range Transparency
Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected base salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipated utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here.
Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram.
**Benefits
**At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here.
Our Commitment to Diversity and Inclusion
At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.
Compliance
If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.