Databricks Enterprise RBAC

Overview

Implement access control across Databricks using Unity Catalog privileges, workspace-level entitlements, and SCIM-provisioned groups. Unity Catalog enforces a three-level namespace (catalog.schema.table) with privilege inheritance, so granting USAGE on a catalog cascades to its schemas.

Prerequisites

• Databricks Premium or Enterprise tier with Unity Catalog enabled
• Account-level admin access for SCIM and group management
• Identity Provider supporting SAML 2.0 and SCIM 2.0

Instructions

Step 1: Create Account-Level Groups via SCIM

# Provision groups that map to IdP teams
databricks account groups create --json '{
  "displayName": "data-engineers",
  "entitlements": [{"value": "workspace-access"}, {"value": "databricks-sql-access"}]
}'

databricks account groups create --json '{
  "displayName": "data-analysts",
  "entitlements": [{"value": "workspace-access"}, {"value": "databricks-sql-access"}]
}'

Step 2: Grant Unity Catalog Privileges

-- Data Engineers: full ETL access to bronze/silver, read gold
GRANT USAGE ON CATALOG analytics TO `data-engineers`;
GRANT CREATE, MODIFY, SELECT ON SCHEMA analytics.bronze TO `data-engineers`;
GRANT CREATE, MODIFY, SELECT ON SCHEMA analytics.silver TO `data-engineers`;
GRANT SELECT ON SCHEMA analytics.gold TO `data-engineers`;

-- Analysts: read-only on curated gold tables
GRANT USAGE ON CATALOG analytics TO `data-analysts`;
GRANT SELECT ON SCHEMA analytics.gold TO `data-analysts`;

Step 3: Apply Cluster Policies

{
  "name": "analyst-serverless-only",
  "definition": {
    "cluster_type": { "type": "fixed", "value": "sql" },
    "autotermination_minutes": { "type": "range", "maxValue": 30 },
    "num_workers": { "type": "range", "maxValue": 4 }
  }
}

Assign the policy to data-analysts so they cannot spin up expensive GPU clusters.

Step 4: Configure SQL Warehouse Permissions

databricks permissions update sql/warehouses WAREHOUSE_ID --json '[
  {"group_name": "data-analysts", "permission_level": "CAN_USE"},
  {"group_name": "data-engineers", "permission_level": "CAN_MANAGE"}
]'

Step 5: Audit with System Tables

SELECT event_time, user_identity.email, action_name, request_params
FROM system.access.audit
WHERE action_name LIKE '%Grant%' OR action_name LIKE '%Revoke%'
  AND event_date > current_date() - INTERVAL 30 DAYS
ORDER BY event_time DESC;

Error Handling

Examples

Basic usage: Apply databricks enterprise rbac to a standard project setup with default configuration options.

Advanced scenario: Customize databricks enterprise rbac for production environments with multiple constraints and team-specific requirements.

Output

• Configuration files or code changes applied to the project
• Validation report confirming correct implementation
• Summary of changes made and their rationale

Resources

• Official logging documentation
• Community best practices and patterns
• Related skills in this plugin pack