Run dbt models on Amazon Redshift directly from a Git repository

Source

yaml

id: dbt-redshift
namespace: company.team

tasks:
  - id: git
    type: io.kestra.plugin.core.flow.WorkingDirectory
    tasks:
      - id: clone_repository
        type: io.kestra.plugin.git.Clone
        url: https://github.com/kestra-io/dbt-example
        branch: main

      - id: dbt
        type: io.kestra.plugin.dbt.cli.DbtCLI
        taskRunner:
          type: io.kestra.plugin.scripts.runner.docker.Docker
        containerImage: ghcr.io/kestra-io/dbt-redshift:latest
        profiles: |
          my_dbt_project:
            outputs:
              dev:
                type: redshift
                host: myhostname.us-east-1.redshift.amazonaws.com
                user: "{{ secret('REDSHIFT_USER') }}"
                password: "{{ secret('REDSHIFT_PASSWORD') }}"
                port: 5439
                dbname: analytics
                schema: dbt
                autocommit: true # autocommit after each statement
                threads: 8
                connect_timeout: 10
            target: dev
        commands:
          - dbt deps
          - dbt build

About this blueprint

Data

This workflow runs dbt against an Amazon Redshift data warehouse by pulling a dbt project from Git and executing it inside a Docker container.

It’s a simple and reliable way to:

Keep dbt projects version-controlled in Git
Run dbt deps and dbt build without managing local environments
Execute transformations directly on Redshift using standard dbt profiles
Reuse the same setup across development, staging, and production

All Redshift connection details are defined in the dbt profile and injected securely via secrets, so credentials never live in the repository.

This pattern works well for analytics engineering teams who want a clean, repeatable way to run dbt on Amazon Redshift, whether on a schedule, as part of CI/CD, or triggered by upstream data pipelines.

Working Directory

Clone

Dbt CLI

Docker

More Related Blueprints

Data

Run Parallel ETL Ingestion with Airbyte to Sync Multiple Data Sources

Data

Bulk Load CSV Data into PostgreSQL Using COPY for Fast ETL Ingestion

Data

Run dbt ELT pipelines on MotherDuck from Git using Docker

New to Kestra?

Use blueprints to kickstart your first workflows.

Get started with Kestra