How to Configure RBAC in BigQuery

How do I configure and manage RBAC roles in BigQuery?

RBAC in BigQuery lets you control who can query, update, or administer datasets, tables, and routines by granting predefined or custom roles at the project, dataset, or object level.

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Description

Example H2

Example H3

What is RBAC in BigQuery?

Role-Based Access Control (RBAC) in BigQuery is Google Cloud IAM applied to datasets, tables, and routines. You grant roles—collections of permissions—to principals (users, groups, or service accounts) to control read, write, and admin actions.

Which roles are available?

BigQuery offers predefined roles such as roles/bigquery.dataViewer, roles/bigquery.dataEditor, and roles/bigquery.admin. You can also create custom roles that bundle only the permissions you need.

How do I grant a role on a dataset?

Use bq update --dataset_access or the Cloud Console to add a { "userByEmail": "dev@acme.com", "role": "roles/bigquery.dataEditor" } entry to the dataset’s ACL. This lets a developer edit tables but not manage the project.

Can I apply RBAC at the table level?

Yes. Authorized views or column-level security policies can restrict access per table or even per column, while keeping dataset-wide roles broader.

How do I audit role changes?

Enable Cloud Audit Logs for BigQuery. Each SetIamPolicy call records the actor, timestamp, and new bindings—crucial for security reviews.

How do I remove a role safely?

First, list current bindings with gcloud projects get-iam-policy. Remove only the specific member/role pair, then test affected workloads in staging before production rollout.

When should I use custom roles?

Create custom roles when predefined roles are too broad. For example, a role that allows bigquery.jobs.create and bigquery.tables.get, but not bigquery.tables.update, fits read-only analytics services.

Best practices for RBAC?

Grant least privilege—start with viewer roles, then add permissions as required.
Use groups or service accounts, not individual emails, to simplify management.
Automate IAM via Terraform or Deployment Manager for repeatability.
Review roles quarterly; remove dormant principals.

Why How to Configure RBAC in BigQuery is important

How to Configure RBAC in BigQuery Example Usage


-- Give the analytics group read-only access to the Orders and Customers tables
GRANT `roles/bigquery.dataViewer`
ON DATASET `ecommerce-project.sales`
TO `group:analytics@acme.com`;

-- Create a view that shows only non-PII customer columns
CREATE OR REPLACE VIEW `ecommerce-project.sales.vw_public_customers` AS
SELECT id, name, created_at
FROM `ecommerce-project.sales.Customers`;

-- Grant public view access
GRANT `roles/bigquery.dataViewer`
ON TABLE `ecommerce-project.sales.vw_public_customers`
TO `allAuthenticatedUsers`;

How to Configure RBAC in BigQuery Syntax


-- Grant a predefined role at the project level
GRANT `roles/bigquery.dataViewer`
ON PROJECT `ecommerce-project`
TO `group:analytics@acme.com`;

-- Grant a custom role at the dataset level
GRANT `roles/bigquery.orderManager`
ON DATASET `ecommerce-project.sales`
TO `serviceAccount:etl@ecommerce-project.iam.gserviceaccount.com`;

-- Revoke a role
REVOKE `roles/bigquery.dataViewer`
ON PROJECT `ecommerce-project`
FROM `user:old_dev@acme.com`;

Common Mistakes

Granting project-level roles when only dataset access is required. This over-privileges users. Fix by scoping the GRANT to the specific dataset or table.
Assigning roles to individual emails instead of groups. This creates maintenance overhead. Fix by using Google Groups or service accounts to aggregate principals.