Securing Customer Emails with Data Masking in Snowflake

Learning Objectives

Create and manage Snowflake roles with appropriate access privileges.

Create users and assign roles with defined default roles and secure passwords.

Develop and implement data masking policies using role-based logic.

Validate data masking by querying tables under different roles.

Overview

In today’s data-driven world, protecting sensitive customer information is more critical than ever. GlobalMart, a leading e-commerce giant operating across 120 markets, faces the real-world challenge of securing customer emails and payment details without sacrificing data accessibility for its diverse teams.

This hands-on scenario puts you in the shoes of Vinay, a Junior Data Engineer, tasked with implementing dynamic data masking in Snowflake — a powerful way to control exactly who sees what, down to the very column level.

You will start from scratch by:

Defining roles with granular access permissions
Creating and managing users assigned to multiple roles
Developing intelligent masking policies that safeguard sensitive data without hindering collaboration
Applying these policies directly to tables and validating their effectiveness in real-time

Dive into the essentials of data governance by creating flexible masking rules that adapt based on user roles. Through this scenario, you’ll learn how to balance security and usability, empowering teams with the data they need — without compromising privacy.

Prerequisites

Basic understanding of Snowflake objects such as databases, schemas, tables, roles, and users.
Understanding of role-based access control (RBAC) principles and privilege assignment in Snowflake.
Awareness of Snowflake’s data masking features and how to create masking policies.