Scaling fine-grained access control for enterprise lakehouse using SageMaker Unified Studio and AWS Lake Formation

This article demonstrates how to implement scalable fine-grained access control for enterprise lakehouses using AWS Lake Formation tag-based access control, IAM Identity Center, and SageMaker Unified Studio with automated governance workflows.

• Combine Lake Formation tag-based access control (TBAC) with IAM Identity Center groups and trusted identity propagation for consistent governance across analytics engines
• Use four-dimension LF-Tag taxonomy (domain, region, data_class, layer) to classify datasets and enforce multi-dimensional authorization policies
• Deploy seven AWS CDK stacks that automate tag assignment and permission provisioning through metadata-driven Lambda functions
• Implement tag inheritance at database and table levels so new datasets automatically inherit governance policies without manual updates
• Validate access control with test users across different domains (US Commercial, EU Clinical Research, Regulatory) confirming proper isolation
• Audit all data access through CloudTrail, resolving IAM Identity Center user identities to meet compliance requirements (HIPAA, GDPR, FDA)

This architecture eliminates manual per-table permission grants, scales governance with dataset growth, and provides complete auditability for enterprise lakehouse environments.