Description

Introduction

As data pipelines grow in complexity, integrating DevOps principles like CI/CD and version control becomes essential for efficiency, quality, and collaboration. This course focuses on applying DevOps practices within Matillion ETL environments, helping teams streamline development, deployment, and governance through automation, source control, and repeatable processes.

Prerequisites

• Experience with Matillion ETL job development

• Familiarity with Git or other version control systems

• Basic understanding of CI/CD workflows

• Knowledge of DevOps tools like Jenkins, GitHub Actions, or Azure DevOps

Table of Contents

1. Introduction to DevOps in the Data World
    1.1 DevOps for Data Engineering Explained
    1.2 Benefits of CI/CD in ETL Projects
    1.3 Matillion’s Role in a DevOps Pipeline

2. Version Control for Matillion Projects
    2.1 Exporting and Importing Jobs as JSON
    2.2 Structuring Git Repositories for ETL
    2.3 Collaborative Job Development with Git

3. Using Matillion API for Automation
    3.1 Overview of Matillion REST APIs
    3.2 Automating Job Export/Import
    3.3 Triggering Jobs Remotely

4. CI/CD Pipeline Setup for ETL Jobs
    4.1 Sample CI/CD Architecture with GitHub Actions
    4.2 Automating Job Deployment to Multiple Environments
    4.3 Handling Secrets and Configurations Securely

5. Job Parameterization and Environment Management
    5.1 Dynamic Parameter Handling
    5.2 Environment-Specific Variables and Settings
    5.3 Promoting Jobs Across Staging, QA, and Production

6. Testing ETL Workflows
    6.1 Writing Unit Tests for SQL and Components
    6.2 Automating Validation Checks
    6.3 Capturing Failures in CI Pipelines

7. Auditing, Rollbacks, and Change Control
    7.1 Tracking Job Changes Over Time
    7.2 Creating Restore Points and Tags
    7.3 Rollback Strategies with Git and JSON

8. Integration with DevOps Tools
    8.1 Jenkins for Pipeline Automation
    8.2 GitLab CI and Azure DevOps Examples
    8.3 Monitoring Deployments and Job Status

9. Best Practices for ETL DevOps
    9.1 Modular Job Design for Maintainability
    9.2 Continuous Documentation Generation
    9.3 Alerts, Logs, and Slack Integration

10. Real-World CI/CD Example with Matillion
    10.1 Building a CI/CD Pipeline from Scratch
    10.2 Deploying Jobs to Redshift/Snowflake
    10.3 Validation, Promotion, and Monitoring

Bringing DevOps practices into Matillion ETL helps data teams work faster, more collaboratively, and with fewer errors. With automated CI/CD pipelines and version-controlled workflows, you can confidently scale and maintain your ETL infrastructure across cloud environments.