Medallion Architecture in Snowflake: A Best Practices Guide

Overview

In today’s data-driven world, organizations need a scalable, secure, and reliable framework to manage data from raw ingestion to actionable insights. But raw data is often messy, inconsistent, and difficult to manage without a clear framework.

That’s where a Medallion Architecture comes in.

As Snowflake experts, we always implement a Medallion architecture thanks to Snowflake’s scalable architecture. The purpose of this article is to provide our best practices when we implement Snowflake for our clients.

What is a Medallion Architecture?

A Medallion Architecture is a multi-layered approach to data engineering that ensures data quality, security, and performance at every stage of the data journey. By structuring data into progressive layers— Bronze, Silver, Gold —businesses can build reliable, scalable, and analytics-ready pipelines on Snowflake’s cloud-native platform.

Key Layers of a Snowflake Medallion Architecture

To implement Medallion Architecture in Snowflake, we recommend structuring data into five distinct schemas across development and production environments:

1. EDP_SOURCE (Raw Zone) – Raw data landing zone housing all source system tables. 
2. EDP_STAGING (Transformation Zone) – Temporary processing area for data transformations.  
3. EDP_MODELLED (Structured Zone) – Clean, structured tables ready for business consumption.  
4. EDP_PUBLISHED (Curated Zone) – Curated views designed for external access and sharing.  
5. EDP_REPORTING (Analytics Zone) – Optimized datasets for analytics and reporting needs. 

Best Practices for Success

When building a Medallion Architecture in Snowflake, keep these best practices in mind:

• Separate Development & Production: Maintain distinct environments for lifecycle management and governance.
• Enforce Data Lineage: Use raw zones to preserve source fidelity and ensure downstream trust.
• Optimize Performance: Leverage Snowflake’s clustering, materialized views, and caching in the reporting layer.
• Enable Secure Sharing: Publish curated data products via Snowflake’s secure data sharing.
• Automate Pipelines: Integrate orchestration tools (e.g., dbt, Airflow, Orchestra) for continuous transformation and deployment.

Summary

Now you’re ready to implement a scalable and secure Medallion Architecture in Snowflake to turn messy raw data into actionable business insights. This best practices guide is vetted from our 20+ Snowflake implementations.

Evaluating your Snowflake architecture? Speak to a Snowflake expert today.