Summary and recommendation
Google BigQuery does not provide direct SCIM provisioning capabilities. As a Google Cloud service, BigQuery user management operates through Google Cloud Identity and IAM roles rather than its own provisioning system. While you can provision users to Google Workspace or Google Cloud Identity via SCIM from identity providers like Okta or Entra ID, BigQuery access must then be manually configured through Google Cloud IAM project-level permissions and dataset-specific roles. This creates a two-step provisioning process that leaves gaps in automated lifecycle management.
The indirect provisioning model creates significant operational overhead for data teams. IT admins must first provision users to Google Cloud Identity, then separately manage BigQuery-specific permissions through IAM roles for projects, datasets, and tables. When users change roles or leave the organization, there's no automated way to revoke BigQuery access—it requires manual cleanup across potentially dozens of projects and datasets. For organizations with complex data governance requirements, this manual process creates compliance risks and inconsistent access controls.
The strategic alternative
BigQuery has no native SCIM. Automate offboarding, user access reviews, and license workflows across every app, including the ones without APIs. We maintain the integration layer underneath. You focus on judgment, not plumbing.
Quick SCIM facts
| SCIM available? | No |
| SCIM tier required | N/A |
| SSO required first? | No |
| SSO available? | Yes |
| SSO protocol | Google Cloud Identity (SAML/OIDC) |
| Documentation | Not available |
Supported identity providers
| IdP | SSO | SCIM | Notes |
|---|---|---|---|
| Okta | ✓ | ❌ | Provision users to Google Cloud Identity/Workspace via SCIM. BigQuery access via IAM roles. |
| Microsoft Entra ID | ✓ | ❌ | Federate Entra ID with Google Cloud Identity. SCIM provisioning to Cloud Identity, then IAM for BigQuery. |
| Google Workspace | Via third-party | ❌ | No native support |
| OneLogin | Via third-party | ❌ | No native support |
The cost of not automating
Without SCIM (or an alternative like Stitchflow), your IT team manages BigQuery accounts manually. Here's what that costs:
The BigQuery pricing problem
BigQuery gates SCIM provisioning behind premium plans, forcing significant cost increases for basic user management.
Tier comparison
| Plan | Price | SSO | SCIM |
|---|---|---|---|
| Standard | Pay-per-query and storage | ||
| All tiers | Usage-based pricing |
Provisioning structure
| Plan | Price | SCIM Support |
|---|---|---|
| Standard | Pay-per-query and storage | ❌ No direct SCIM |
| All tiers | Usage-based pricing | ❌ Must use Google Cloud Identity |
BigQuery access requires provisioning users to Google Cloud Identity or Google Workspace first, then assigning specific BigQuery IAM roles for dataset and project access.
What this means in practice
Multi-step provisioning process
1. Provision users to Google Cloud Identity/Workspace via SCIM 2. Manually assign Google Cloud IAM roles for BigQuery access 3. Configure dataset-level and table-level permissions separately 4. Manage project-based access controls through Google Cloud Console
Real workflow complexity
Additional constraints
Summary of challenges
- BigQuery does not provide native SCIM at any price tier
- Organizations must rely on third-party tools or manual provisioning
- Our research shows teams manually provisioning this app spend significant hidden costs annually
What BigQuery actually offers for identity
No Direct SCIM Integration
BigQuery doesn't provide a native SCIM endpoint. As a Google Cloud service, user access is managed through Google Cloud Identity and IAM:
| Feature | Available? |
|---|---|
| Direct BigQuery SCIM | ❌ No |
| User provisioning | Via Google Cloud Identity/Workspace only |
| Group provisioning | Via Google Cloud Identity/Workspace only |
| Access control | Google Cloud IAM roles |
| SSO | Via Google Cloud Identity (SAML/OIDC) |
The reality: To provision users for BigQuery, you must: 1. Provision users to Google Cloud Identity or Google Workspace via SCIM 2. Manually assign BigQuery IAM roles and dataset permissions 3. Manage project-level access separately
Google Cloud Identity SCIM Limitations
Even when using Google Cloud Identity's SCIM endpoint, you face significant constraints:
Translation: You get basic user creation in Google Cloud Identity, but none of the BigQuery-specific access management that data teams actually need. Dataset permissions, project access, and IAM role assignments remain manual processes.
What IT admins are saying
BigQuery's indirect provisioning model through Google Cloud Identity creates complexity for IT teams managing data analytics access:
- No direct SCIM endpoint for BigQuery itself - all user management flows through Google Cloud Identity
- Must provision users to Google Workspace or Cloud Identity first, then assign BigQuery IAM roles separately
- Dataset and table-level permissions require additional Google Cloud IAM configuration beyond basic user provisioning
- Project-based access control adds another layer of complexity for cross-functional data teams
BigQuery is a Google Cloud service. User management via Google Cloud IAM and Cloud Identity. No direct SCIM endpoint - provision users to Google Cloud Identity/Workspace instead.
Must manage via Google Cloud Identity layer
The recurring theme
While BigQuery integrates well within the Google ecosystem, IT teams outside of Google Workspace face a multi-step provisioning process - create users in Google Cloud Identity, assign appropriate IAM roles, then configure dataset-specific permissions for each data analyst or scientist.
The decision
| Your Situation | Recommendation |
|---|---|
| Small data team (<10 analysts) with basic BigQuery needs | Manual Google Cloud IAM management is acceptable |
| Single-project data warehouse with stable team | Manual management with Google Workspace SSO |
| Multi-project enterprise with complex dataset permissions | Use Stitchflow: automate Google Cloud Identity provisioning |
| Large organization (50+ data users) across multiple teams | Use Stitchflow: automation essential for IAM role management |
| Compliance-heavy environment requiring audit trails | Use Stitchflow: automated provisioning with full audit logging |
The bottom line
BigQuery has no direct SCIM endpoint—all user management flows through Google Cloud Identity and IAM roles. While this works for small teams, enterprise data organizations need automated provisioning to handle the complexity of multi-project access and dataset permissions. Stitchflow eliminates the manual overhead of managing Google Cloud Identity provisioning at scale.
Make BigQuery workflows AI-native
BigQuery has no native SCIM. We build complete offboarding, user access reviews, and license workflows across every app, including the ones without APIs.
Technical specifications
SCIM Version
Not specifiedSupported Operations
Not specifiedSupported Attributes
Plan requirement
Not specifiedPrerequisites
Not specifiedKey limitations
- No direct SCIM endpoint for BigQuery
- User provisioning via Google Cloud Identity/Workspace
- Access controlled through Google Cloud IAM roles
- SCIM to Google Workspace limited to users (not groups)
Documentation not available.
Configuration for Okta
Integration type
Okta Integration Network (OIN) app
Where to enable
Docs
Provision users to Google Cloud Identity/Workspace via SCIM. BigQuery access via IAM roles.
Use Stitchflow for automated provisioning.
Configuration for Entra ID
Integration type
Microsoft Entra Gallery app
Where to enable
Federate Entra ID with Google Cloud Identity. SCIM provisioning to Cloud Identity, then IAM for BigQuery.
Use Stitchflow for automated provisioning.
Unlock SCIM for
BigQuery
BigQuery has no native SCIM. We still automate end-to-end workflows across every app, including the ones without APIs.
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