Managing dbt Projects on Snowflake using Snowflake CLI¶

Note

The dbt Projects on Snowflake features in Snowflake CLI are available only in version 3.13.0 or later.

Note

Some features described on this page require a dbt project object that uses the mutable live version. To get a live-version object, opt in to the 2026_06 behavior change bundle or ask your Snowflake account representative to enable the separate single live version feature. Then create or replace the object, or migrate an existing versioned object with SYSTEM$MIGRATE_DBT_PROJECT. For details, see dbt Projects on Snowflake: dbt project objects migrate to a single mutable live version.

You can use Snowflake CLI to manage dbt project objects with the following operations:

Deploying a dbt project object
Listing all available dbt project objects
Executing a dbt project object command
Describing a dbt project object
Dropping a dbt project object
Copying dbt project files

Deploying a dbt project object¶

The snow dbt deploy command uploads local files to a temporary stage and creates a new dbt project object or updates it by replacing its live version in a single operation. A valid dbt project must contain dbt_project.yml and one of the supported profile files:

dbt_project.yml: A standard dbt configuration file that specifies the profile to use.
dbt_projects_profiles.yml or profiles.yml: A dbt connection profile definition referenced in dbt_project.yml. The selected profile file must define the database, role, schema, and type. If both files are present, Snowflake uses dbt_projects_profiles.yml and ignores profiles.yml during deployment, compilation, and subsequent commands.
- By default, dbt Projects on Snowflake uses your target schema (target.schema) specified from your dbt environment or profile. When you execute a dbt project object, dbt attempts to create the target schema specified in dbt_projects_profiles.yml or profiles.yml if it doesn’t already exist. For more information, see Understand schema generation and customization.
```
<profile_name>:
  target: dev
  outputs:
    dev:
      database: <database_name>
      role: <role_name>
      schema: <schema_name>
      warehouse: <warehouse_name>
      type: snowflake
```

The following examples illustrate how to use the snow dbt deploy command:

Warning

Don’t use --force unless you intentionally want to recreate the dbt project object. In snow dbt deploy, --force runs CREATE OR REPLACE DBT PROJECT, which may remove run history.

Deploy a dbt project object named jaffle_shop:
```
snow dbt deploy jaffle_shop
```
Deploy a project named jaffle_shop from a specified directory, using a profile file from a separate directory. The CLI looks for dbt_projects_profiles.yml first and uses profiles.yml only if dbt_projects_profiles.yml isn’t present. The CLI copies the file into the root of the deployed project object with the same filename, overwriting a file with the same name in this location:
```
snow dbt deploy jaffle_shop --source /path/to/dbt/directory --profiles-dir ~/my_profiles/
```

Deploy a project named jaffle_shop from a specified directory, supplying a profile file from outside the project, setting a default target, pinning a dbt version, and enabling external access integrations:

snow dbt deploy jaffle_shop --source /path/to/dbt/directory \
  --profiles-dir ~/my_profiles/ \
  --default-target prod \
  --dbt-version 1.11.11 \
  --external-access-integration dbthub-integration \
  --external-access-integration github-integration

Deploy a project named jaffle_shop and set a specific dbt runtime version:
```
snow dbt deploy jaffle_shop --dbt-version '1.11.11'
```
Deploy a project named jaffle_shop, pull in an env.yml file from a separate directory, and set the default environment for compilation and later executions:
```
snow dbt deploy jaffle_shop --source /path/to/dbt/directory \
  --env-file-dir /path/to/env/directory \
  --default-env prod
```
The --env-file-dir flag points the CLI at an env.yml file elsewhere in your repo (similar to --profiles-dir) and pulls it into the deployed object, overwriting the object’s root env.yml if one already exists. The --default-env flag sets the environment used for compilation and subsequent executions. These flags require Snowflake CLI 3.21 or later. For more information, see Using SQL environment variables and private Git packages for dbt Projects on Snowflake.

Listing all available dbt project objects¶

The snow dbt list command lists all available dbt project objects on Snowflake.

The following examples illustrate how to use the snow dbt list command:

List all available dbt project objects:
```
snow dbt list
```
List dbt project objects in the product database whose names begin with JAFFLE:
```
snow dbt list --like JAFFLE% --in database product
```

Executing a dbt project object command¶

The snow dbt execute command executes one of the following dbt commands (https://docs.getdbt.com/reference/dbt-commands) on a Snowflake dbt project object:

build (https://docs.getdbt.com/reference/commands/build)
clean (https://docs.getdbt.com/reference/commands/clean)
compile (https://docs.getdbt.com/reference/commands/compile)
deps (https://docs.getdbt.com/reference/commands/deps)
list (https://docs.getdbt.com/reference/commands/list)
parse (https://docs.getdbt.com/reference/commands/parse)
retry (https://docs.getdbt.com/reference/commands/retry)
run (https://docs.getdbt.com/reference/commands/run)
run-operation (https://docs.getdbt.com/reference/commands/run-operation)
seed (https://docs.getdbt.com/reference/commands/seed)
show (https://docs.getdbt.com/reference/commands/show)
snapshot (https://docs.getdbt.com/reference/commands/snapshot)
source freshness (https://docs.getdbt.com/reference/commands/source)
test (https://docs.getdbt.com/reference/commands/test)

For more information about using dbt commands, see the dbt Command reference (https://docs.getdbt.com/reference/dbt-commands).

The following examples illustrate how to use the snow dbt execute command:

Execute the dbt test command:
```
snow dbt execute jaffle_shop test
```
Execute the run dbt command asynchronously:
```
snow dbt execute --run-async jaffle_shop run
```
Execute the run dbt command with a specific dbt version:
```
snow dbt execute --dbt-version '1.9.4' jaffle_shop run
```
Execute the run dbt command against a selected environment, overriding individual variables for this run:
```
snow dbt execute --env staging \
  --env-vars '{"DBT_DATABASE": "tasty_bytes_staging_db"}' jaffle_shop run
```
The --env flag selects the environment defined in the project’s env.yml file, and --env-vars applies inline key/value overrides for this execution. Use --use-shell-env-vars to pull DBT_-prefixed shell variables (excluding DBT_ENV_SECRET_* variables) into the run. These flags require Snowflake CLI 3.21 or later. For more information, see Use the Snowflake CLI.

Describing a dbt project object¶

The snow dbt describe command describes a dbt project object on Snowflake.

The following example describes the dbt project object named my_dbt_project on Snowflake:

snow dbt describe my_dbt_project

Dropping a dbt project object¶

The snow dbt drop command deletes a dbt project object on Snowflake.

The following example deletes the dbt project object named my_dbt_project on Snowflake:

snow dbt drop my_dbt_project

Copying dbt project files¶

The snow dbt copy command copies files between local directories, stages, and a dbt project object’s live version. Use snow dbt execute --import instead when files only need to be mounted under ./imports for one execution.

Use `snow dbt` commands in a CI/CD workflow¶

Note

When building CI/CD workflows, you only need your Git server, such as GitHub, and Snowflake CLI. A Git repository object is not required.

You can run dbt commands with Snowflake CLI to test pull requests and update the production dbt project object after changes merge. Choose a workflow based on the amount of the project that CI needs to validate:

Basic CI workflow: Deploy a tester dbt project object and run dbt build across the project. Start with Tutorial: Set up CI/CD integrations on dbt Projects on Snowflake.
Advanced Slim CI: Deploy with automatic compilation disabled, import dbt artifacts from the last successful production execution, and use state selection with defer to process only changed models and their downstream dependencies. For a complete per-pull-request CI workflow, see Tutorial: Set up CI/CD with Slim CI and per-PR databases for dbt Projects on Snowflake.

To build a CI/CD workflow with snow dbt commands, follow these steps:

Prepare your dbt project:
1. Download your dbt project or start a new one.
  - Ensure that the main project directory contains dbt_project.yml and either dbt_projects_profiles.yml or profiles.yml.
  - Verify that the profile name referenced in dbt_project.yml is defined in dbt_projects_profiles.yml or profiles.yml. If both files are present, Snowflake uses dbt_projects_profiles.yml.
    
    Note
    Ensure that credentials are excluded from the profile file. Leave account and user as placeholder strings and let your CI/CD platform supply the connection through secrets or environment variables.
Set up Snowflake CLI GitHub Action.

Follow the guidelines for setting up GitHub Action for Snowflake CLI and verify your connection to Snowflake.
Define your workflow.

The following example illustrates a CI workflow that replaces the live version of the dbt project object named product_pipeline in a single operation, then builds models and runs tests in DAG order:
```
- name: Execute Snowflake CLI command
  run: |
    snow dbt deploy product_pipeline
    snow dbt execute product_pipeline build
```

Managing dbt Projects on Snowflake using Snowflake CLI¶

Deploying a dbt project object¶

Listing all available dbt project objects¶

Executing a dbt project object command¶

Describing a dbt project object¶

Dropping a dbt project object¶

Copying dbt project files¶

Use snow dbt commands in a CI/CD workflow¶

Use `snow dbt` commands in a CI/CD workflow¶