Senior Databricks Security Engineer & AI Automation Engineer
Summary
Hands-on security role in BGC, Taguig: strengthen Databricks platform security (Unity Catalog, access control, secrets, audit logging, CMK) on Azure/AWS and build AI-driven automation for security monitoring and remediation using Python, Terraform, and Splunk in a regulated financial services environment. Hybrid 3x onsite, nightshift.
Job Role: Senior Databricks Security Engineer & AI Automation Engineer
Employment Type: Permanent / Full-time
Working Shift: Nightshift Schedule - 11:00 PM to 5:00 AM
Work Location: BGC, Taguig
Work Setup: Hybrid - 3x onsite per week
We’re looking for a hands-on security professional who can strengthen Databricks platform security while building AI-driven automation for security operations.
Qualifications:
Required
• 5+ years in cloud security, data security, or security engineering, including 2+ years of deep, hands-on Databricks experience in a production enterprise environment.
• Expert-level knowledge of Databricks security features: Unity Catalog and fine-grained access control, workspace and account administration, cluster and compute policies, secrets management, audit logging and system tables, and encryption with customer-managed keys.
• Demonstrated experience with Databricks identity integration (SSO, SCIM, service principals, OAuth) and with the Databricks REST API or SDK for programmatic configuration, auditing, and automation.
• Strong scripting and automation skills in Python (strongly preferred) for building integrations, data pipelines, and reporting automation, plus Infrastructure as Code experience (Terraform preferred).
• Solid understanding of cloud networking and security on Azure and/or AWS: private connectivity, segmentation, storage security, key management, and IAM.
• Experience managing data security and access governance in regulated financial services environments (banking regulatory, GLBA, PCI-DSS, SOX) with demonstrated ability to drive remediation accountability.
• Working knowledge of data protection techniques (classification, masking, tokenization, DLP) and of common risks in data and analytics platforms, including over-permissioned access, credential and token sprawl, and data exfiltration.
• Experience with SIEM integration and log engineering (Splunk preferred) and with ticketing systems (ServiceNow, Jira) for workflow automation.
What to Expect:
✅Build and automate security controls for data and AI platforms
✅Develop AI-driven workflows for security monitoring, investigation, and remediation
✅Work with modern cloud security technologies in a regulated financial services environment