Staff Enterprise Security Engineer

• 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.
• Partners effectively with product and engineering teams to review implementation designs, surface risk early, and drive practical security requirements without owning product delivery.
• Applies strong security judgment to data flows, platform configurations, access patterns, and enterprise data-security decisions on and across the Databricks platform.
• Builds durable automation, monitoring, and tooling that scales EntSec coverage and reduces repeated manual work.
• 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
• 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
• and the benefits listed above. For more information regarding which range your location is in visit our page here.