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Senior Databricks Platform Security Engineer

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Summary

Senior security engineer hardening a Databricks platform for a digital financial institution: designing security architecture, managing Unity Catalog and IAM, integrating audit logs with Splunk, automating controls with Python/Terraform, and building AI agents for security workflows.

Salary: ₱120,000 – ₱145,000 per month

Work Setup: Project-hire | Dedicated Client Deployment
Industry: Digital Financial Institution
Team: Cybersecurity

Key Responsibilities

  • Design, implement, and maintain security architecture and controls across the Databricks platform.

  • Manage Unity Catalog, identity and access management, workspace security, and data governance.

  • Develop AI-powered agents to automate security workflows, access reviews, risk assessments, and audit reporting.

  • Implement security monitoring and integrate Databricks audit logs with SIEM platforms such as Splunk.

  • Automate security configurations and controls using Python, Terraform, and Databricks APIs.

  • Collaborate with data engineering, cloud, and cybersecurity teams to address security risks and ensure compliance.

Qualifications

  • At least 5 years of experience in Cloud Security, Data Security, or Security Engineering.

  • Minimum of 2 years of hands-on Databricks experience in an enterprise environment.

  • Strong knowledge of Databricks security features, particularly Unity Catalog, access controls, workspace administration, and audit logging.

  • Proficiency in Python scripting and automation; Terraform experience is preferred.

  • Experience with Azure and/or AWS cloud security, networking, IAM, and data protection.

  • Familiarity with financial services security requirements and regulatory frameworks such as PCI-DSS, SOX, and GLBA.

  • Experience with SIEM tools, preferably Splunk.

Preferred Qualifications

  • Experience developing AI/LLM-powered security automation or agent-based workflows.

  • Familiarity with prompt engineering, AI orchestration frameworks, and MCP.

  • Databricks, Azure, AWS, or cloud security certifications.

  • Experience securing machine learning and Generative AI workloads.


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