Coordinating dbt runs with upstream ingestion and downstream consumption often requires complex solutions and different tools. You can now add a dbt job activity (Preview) directly to your Fabric pipelines. This lets you orchestrate dbt transformations alongside other pipeline activities, so you can build end-to-end data workflows without switching tools.
Why this matters
- Run dbt jobs as part of your pipeline — chain dbt with other activities using dependency conditions.
- Create or select dbt jobs inline — select an existing dbt job or create one without leaving the pipeline canvas.
- Parameterized workflows — pass dynamic runtime parameters from your pipeline to the dbt job, enabling reusable, parameterized workflows.
- Get notified when jobs finish — send Teams or email notifications after each dbt run.
- Monitor progress in one place — track dbt job status directly within your pipeline run history.
How to use dbt job activity
- Open or create a data pipeline in your Fabric workspace.
- Add the dbt job activity from the activity pane.
- On the Settings tab, configure or select a connection to the workspace that contains your dbt job. You can use an existing connection or create a new one through the Get data page.
- Select the target workspace and dbt job item. If you don't have a dbt job yet, select + New to create one inline.
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Figure: Add dbt job activity.
Parameterized workflows in dbt job
Dynamic content can be used to parameterize all columns in the Settings tab. By adding dynamic content, you can set parameters for any dbt job activity property. All columns in the Settings tab support dynamic content.For instance, you can pass a parameter to the Select field, allowing each pipeline run to execute only the models that meet the specified rules.
Figure: Configure dynamic content for dbt job.
Advanced settings for dbt job
- The Settings tab provides access to advanced options for dbt command settings, node selection, and execution behavior.
- Select your dbt command (build, run, compile, snapshot, or test) and set filters such as select, exclude, full refresh, or fail fast as needed.
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Figure dbt job advanced settings.
Next steps
By integrating dbt jobs into Fabric pipelines, you can orchestrate transformations alongside other pipeline activities and manage orchestration logic in a single workflow. This Preview capability is designed to reduce complexity while giving you more control and visibility over dbt execution. Try it out in your pipelines and share feedback in the comment section to help guide what comes next.- Orchestrate dbt jobs in Fabric data pipelines — explore the full setup and configuration guide.
- Monitor pipeline runs in Microsoft Fabric — track your dbt job runs.