PCI DSS requirements demand tight control over who can see cardholder data, how they authenticate, and what permissions they have. For Databricks, that means aligning clusters, jobs, notebooks, and data sources with principle-of-least-privilege rules. The platform’s flexibility makes it powerful, but without discipline, it becomes a compliance liability.
Start with scoping. Identify all workspaces, tables, and files holding PCI data. Use object tagging and workspace separation to isolate regulated datasets. Every path that touches cardholder data must fall under PCI DSS controls.
Then lock down role-based access control (RBAC). Assign privileges at the smallest necessary scope—cluster-level for compute, table-level for data, and notebook-level for code execution. Avoid granting “All Users” or “Can Manage” permissions unless essential. Use strong authentication, integrate with Azure AD or AWS IAM, and enforce MFA for all accounts with data access.
Audit relentlessly. Databricks provides access logs and audit logs; pipe them to a SIEM and set alerts for unusual access patterns. PCI DSS requires periodic review and proof of enforcement—store reports, configurations, and evidence in a secure repository.