Description

Introduction

This hands-on course is designed for data professionals who want to build efficient, scalable data pipelines using Matillion ETL and Snowflake. From ingestion to transformation and loading into Snowflake, you’ll learn how to architect a complete data workflow in the cloud. The course covers real-world scenarios, automation techniques, and performance optimization strategies to help you move from raw data to business-ready insights quickly and reliably.

Prerequisites

• Familiarity with SQL

• Basic understanding of ETL/ELT concepts

• Exposure to cloud computing environments

• Optional: Basic experience with Matillion and Snowflake UI

Table of Contents

1. Introduction to the Matillion + Snowflake Ecosystem
    1.1 Overview of Matillion ETL Architecture
    1.2 Understanding Snowflake’s Cloud-Native Design
    1.3 Benefits of Integration for Modern Data Teams

2. Setting Up Your Environment
    2.1 Creating a Snowflake Account and Warehouse
    2.2 Launching and Configuring Matillion for Snowflake
    2.3 Managing Connections and Environments

3. Data Ingestion Techniques
    3.1 Loading Files from S3, Azure Blob, or GCS
    3.2 Connecting to On-Premise and SaaS Sources
    3.3 Using Query and API Components for Live Data Pulls

4. Data Staging and Landing Zones
    4.1 Best Practices for Raw and Staging Layers
    4.2 Creating and Managing External Tables
    4.3 Leveraging Snowflake’s File Format and COPY Options

5. Data Transformation in Matillion
    5.1 Transformation Components: Join, Filter, Calculator
    5.2 Handling Complex Business Logic in SQL
    5.3 Using Temporary and Persistent Tables

6. Data Loading into Snowflake
    6.1 Managing Bulk and Incremental Loads
    6.2 Automating Data Merges (SCD1/SCD2)
    6.3 Using Snowflake Streams and Tasks with Matillion

7. Job Orchestration and Automation
    7.1 Designing Workflows with Orchestration Jobs
    7.2 Scheduling Pipelines and Triggering Jobs
    7.3 Using Parameters and Variables Across Jobs

8. Monitoring, Logging, and Error Handling
    8.1 Monitoring Job Status and Runtime Logs
    8.2 Setting Up Notifications and Retry Logic
    8.3 Capturing Audit Trails and Metadata

9. Performance Optimization Tips
    9.1 Snowflake Warehouse Sizing and Auto-Suspend
    9.2 Partitioning and Clustering Best Practices
    9.3 Query Profiling in Snowflake and Matillion

10. Real-World Use Cases
    10.1 Sales and Marketing Data Pipeline
    10.2 IoT Analytics with Time-Series Data
    10.3 Data Pipeline for Financial Reporting

Combining the strengths of Matillion and Snowflake allows you to build powerful, end-to-end cloud data pipelines with minimal complexity and maximum scalability. This course equips you to handle data ingestion, transformation, orchestration, and performance tuning with confidence—enabling faster delivery of insights and greater business impact.