How to Perform BigQuery Integration with dbt in PostgreSQL

Galaxy Glossary

How do I connect dbt to BigQuery and run incremental models?

Connect dbt to BigQuery so you can version-control, test, and deploy analytics code with modern engineering workflows.

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Description

Example H2

Example H3

What does dbt-BigQuery integration do?

dbt compiles your model .sql files into BigQuery-native SQL, executes them, and stores results in datasets you configure. You gain CI/CD, testing, documentation, and lineage on top of BigQuery’s serverless engine.

Which IAM roles must I grant?

Give the service account BigQuery Data Editor on the target dataset, BigQuery Job User at the project level, and BigQuery Read Session User if you use Python materializations.Minimum roles keep security tight.

How do I create profiles.yml for BigQuery?

Add a profile with type: bigquery, method: service-account, project, dataset, threads, timeout_seconds, and keyfile path. Place profiles.yml in ~/.dbt or set DBT_PROFILES_DIR.

How do I model ecommerce tables?

Create models/orders_summary.sql that selects order_id, customer_id, order_date, total_amount, joins Customers and aggregates OrderItems. Tag it as materialized = incremental.

How do I seed reference data?

Put CSVs in the /seeds folder—e.g., product_categories.csv. Run dbt seed to load into BigQuery.Version control keeps seed data auditable.

How do I run and test models?

Run dbt run to build models, dbt test to execute assertions like accepted_values or relationships on Orders.customer_id → Customers.id.

How do I schedule production jobs?

Use Cloud Composer or Cloud Build to call dbt run with the --project-dir and --profiles-dir flags.Or deploy a Dagster/Airflow DAG that invokes the dbt CLI container.

Best practices for BigQuery + dbt?

Use incremental models for large fact tables, enable partition_by and cluster_by configs, keep datasets environment-scoped (dev, prod), and add column tests to catch schema drift early.

How do I debug failed jobs?

Check the BigQuery Job ID printed in the dbt log, open it in the console, and inspect slot usage or SQL compilation outputs in target/compiled.

Why How to Perform BigQuery Integration with dbt in PostgreSQL is important

How to Perform BigQuery Integration with dbt in PostgreSQL Example Usage


-- Build an incremental summary of yesterday's orders
dbt run --select orders_summary --vars '{"run_date": "2024-06-04"}'
-- Validate foreign-key relationships
dbt test --model Orders --store-failures

How to Perform BigQuery Integration with dbt in PostgreSQL Syntax


# profiles.yml (excerpt)
my_bigquery:
  target: dev
  outputs:
    dev:
      type: bigquery
      method: service-account
      project: analytics-dev-123
      dataset: ecommerce_dev
      keyfile: /path/to/keyfile.json
      threads: 4
      timeout_seconds: 300

# dbt commands
$ dbt debug                           # verify connection
$ dbt run --select orders_summary     # build specific model
$ dbt test --exclude tag:incremental  # run tests except incremental models
$ dbt run-operation stage_external_sources  # optional macro

# Model example (models/orders_summary.sql)

SELECT o.id              AS order_id,
       o.customer_id,
       o.order_date,
       o.total_amount,
       c.name            AS customer_name,
       COUNT(oi.id)      AS item_count
FROM  o
JOIN  c ON c.id = o.customer_id
LEFT JOIN  oi ON oi.order_id = o.id
{% if is_incremental() %}
  WHERE o.order_date >= DATE_SUB(CURRENT_DATE(), INTERVAL 1 DAY)
{% endif %}
GROUP BY 1,2,3,4,5;

Common Mistakes

Granting the service account Owner role. This over-permissions the account and violates least privilege. Instead, assign BigQuery Data Editor on the dataset and Job User on the project.
Forgetting to set partition_by on incremental models. Without partitions, BigQuery rewrites entire tables, leading to high costs. Add partition_by config to update only new data.

Frequently Asked Questions (FAQs)

Does dbt work with BigQuery’s on-demand or flat-rate pricing?

dbt is compute-agnostic. Your project’s billing settings—on-demand slots or flat-rate—apply to the queries dbt submits.

How do I handle secrets in CI pipelines?

Store the service-account JSON in a secret manager and mount it at build time, or pass credentials via environment variables supported by profiles.yml.