What's changing in the dbt Analytics Engineering Certification Exam?

Let's go through the 4 biggest changes in the new exam outline and access our updated Study Guide.

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Notes from the state method documentation.

If you tuned into the dbt Coalesce in Oct 2025, you likely joined me in wondering when those new features would make their way into the dbt Analytics Engineering Certification Exam.

In late 2025, dbt released dbt Core v1.11, and, sure enough, as of 20th May 2026, the exam will begin targeting this version. Naturally, this impacted the new exam outline and what you should focus on while preparing for the exam.

In this post, I am going to outline these changes and what this means for our own updated Study Guide.

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The new dbt Core v1.11: dbt wants to be more than a SQL transformation tool

More than just introducing new features, the new dbt Core is evolving from a mere SQL transformation framework to become a production analytics engineering platform.

The release article states that dbt is now catering to the needs of teams who want to:

• standardise logic across their data stack

• understand when they're adhering to the dbt standard and when they're doing something custom

• benefit from better debugging and performance optimisations

With this evolution, the exam naturally evolved as well.

Knowing how to use the standard features of dbt is no longer enough to get certified - those topics now sit mostly in the “fundamentals” layer.

Now, the expectation is that you understand how dbt behaves inside a real production pipeline: orchestration, state-aware execution, testing strategy, governance, incremental processing, failure handling, and operational troubleshooting.

The focus has shifted from “Can you build dbt models?” to “Can you operate dbt reliably as part of a larger data product?”

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What’s changing in the exam outline?

Although the biggest new feature of dbt Core v1.11 is the UDFs, this has yet to make the exam outline. However, there are still substantial changes that all aspiring certified developers should be mindful of.

The Study Guide has been fully updated to reflect these changes.

Source

1. The Fundamentals have expanded

What dbt considers as fundamental knowledge has changed.

Previously, the first Checkpoint was a deep-dive into the simplest parts of dbt, like sources and models - with a dedicated section to using SQL in business logic and git functionality.

Now, with the evolving state of data pipelines in the real world, dbt adds incremental materializations, snapshots and advanced flags to the Fundamentals.

Therefore, as a starting point, you should become very familiar with all the functionalities that dbt offers.

2. Increased focus on model governance and debugging

As dbt places itself as more than a SQL transformation tool, certified developers should know how to use its functionalities to prevent errors from happening and, when they do happen, to catch them early on.

Model access, versioning and contracts were already part of the previous exam. Debugging also had a light focus.

Now, besides covering these as functionalities, the new exam outline expects you to know of best practices and how to use flags to effectively catch errors before they hit production.

3. Testing on steroids: unit tests are now part of the exam

Testing has always been an important part of the dbt infrastructure and this has not changed.

In the new outline, unit testing is added as a topic. But not only that, certified developers should know how to create an efficient testing strategy that serves their data product.

4. Decreased focus on dbt docs and advanced deployment

While the topics above have become more important, dbt has decreased the focus on documentation and advanced deployment.

In the new outline, dbt docs is still mentioned as part of the long list of funcionalities under Fundamentals but with a much smaller focus than before.

As for advanced deployement, topics like environment variables, custom schema, and hooks have disappeared from the outline.

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