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Dagster & dbt Cloud

info

This feature is considered in a beta stage. It is still being tested and may change. For more information, see the API lifecycle stages documentation.

Dagster allows you to run dbt Cloud jobs alongside other technologies. You can schedule them to run as a step in a larger pipeline and manage them as a data asset.

Installation​

uv add dagster-dbt

Example​

import os

from dagster_dbt import dbt_cloud_resource, load_assets_from_dbt_cloud_job

import dagster as dg

# set the auth token as an env var for demo purposes
os.environ["DBT_CLOUD_AUTH_TOKEN"] = "abc"

# configure a resource to connect to your dbt Cloud instance
dbt_cloud = dbt_cloud_resource.configured(
    {"auth_token": {"env": "DBT_CLOUD_AUTH_TOKEN"}, "account_id": 11111}
)

# import assets from dbt
dbt_cloud_assets = load_assets_from_dbt_cloud_job(
    dbt_cloud=dbt_cloud,
    job_id=33333,
)

defs = dg.Definitions(assets=[dbt_cloud_assets])

About dbt Cloud​

dbt Cloud is a hosted service for running dbt jobs. It helps data analysts and engineers productionize dbt deployments. Beyond dbt open source, dbt Cloud provides scheduling , CI/CD, serving documentation, and monitoring & alerting.

If you're currently using dbt Cloud™, you can also use Dagster to run dbt-core in its place. You can read more about how to do that here.