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Advanced Data Engineering with Snowflake

IntermediateSkill Level
Updated 06/2026
Build reliable Snowflake pipelines with DevOps and observability: Git, CI/CD, and Snowflake Trail monitoring.
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SnowflakeData Engineering
3 hr
23 videos
38 Exercises
1,900 XP
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Course Description

Take your Snowflake data pipelines to production with DevOps and observability. In this hands-on course, you'll implement source control with Git, manage database changes declaratively using CREATE OR ALTER, and automate deployments with the Snowflake CLI and GitHub Actions. Then you'll make pipelines observable with Snowflake Trail, using event tables, logging, traces, alerts, and notifications to monitor pipeline health and respond quickly when issues arise. By the end, you'll be able to build, deploy, and maintain reliable pipelines that scale with modern demands.

What you'll learn

  • Differentiate the core DevOps practices for data engineering and the role of Git source control in building Snowflake pipelines collaboratively.
  • Assess how the Snowflake CLI and GitHub Actions automate continuous delivery of pipeline changes across staging and production environments.
  • Identify how Snowflake Trail uses alerts and notifications to monitor pipeline health and prompt action when issues arise.

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Prerequisites

Introduction to Modern Data Engineering with Snowflake
1

DevOps with Snowflake

Learn how to apply DevOps best practices to Snowflake data pipelines, from source control with Git to declarative database changes with CREATE OR ALTER and automated CI/CD using the Snowflake CLI and GitHub Actions.
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2

Observability with Snowflake

In this final chapter, you'll learn how to make data pipelines observable with Snowflake Trail, using event tables, logging, traces, alerts, and notifications to monitor pipeline health and act on issues quickly.
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Advanced Data Engineering with Snowflake
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