Notion + Bruin

Source

Ingest Notion data into your warehouse with incremental loading, quality checks, and full lineage. Defined in YAML, version-controlled in Git.

For business teams

What you get

Operational analytics
Notion data in your warehouse means analytics that Notion's built-in reporting can't provide. Cross-tool, cross-team, custom.
Cross-tool project views
Combine Notion with Jira, GitHub, Slack, and other tools. One dashboard that shows the real state of projects.
Team workload insights
Understand collaboration patterns, bottlenecks, and workload distribution from Notion data — automatically updated.
No manual data pulling
Notion data syncs on schedule. Managers and leads get fresh data without asking anyone.

For data & engineering teams

How it works

Incremental sync
Only sync new and changed Notion records. No full reloads, no wasted compute.
YAML-defined, Git-versioned
Your Notion pipeline is a YAML file. Review in PRs, deploy with CI/CD, roll back with git revert.
Schema change handling
Bruin detects Notion schema changes automatically. No manual intervention when fields get added or renamed.
Cross-tool joins
Combine Notion data with other tools in SQL transforms. Bruin resolves dependencies across sources automatically.

Before you start

Notion workspace with databases

Integration created and connected to workspace

Database shared with integration

API token generated

Step 1

Add your Notion connection

Notion API connection using integration token. Add this to your Bruin environment file — credentials are stored securely and referenced by name in your pipeline YAML.

Parameters

api_keyIntegration token from Notion
database_idID of the Notion database

connections:
  notion:
    type: notion
    uri: "notion://api_key@database_id"

Step 2

Create your pipeline

Define a YAML asset that tells Bruin what to pull from Notion and where to land it. This file lives in your Git repo — reviewable, version-controlled, and deployable with CI/CD.

Available tables

TasksProjectsContactsContent Calendar

name: raw.notion_Tasks
type: ingestr

parameters:
  source_connection: notion
  source_table: 'Tasks'
  destination: bigquery

Step 3

Add quality checks

Add column-level and custom SQL checks to your Notion data. If a check fails, the pipeline stops — bad data never reaches downstream models or dashboards.

Validate workspace data synced completely

Ensure record IDs are unique and titles are present

Catch missing or null fields on every sync

columns:
  - name: id
    checks:
      - name: not_null
      - name: unique
  - name: title
    checks:
      - name: not_null

custom_checks:
  - name: workspace sync is complete
    query: |
      SELECT COUNT(*) > 0
      FROM raw.notion_Tasks

Step 4

Run it

One command. Bruin connects to Notion, pulls data incrementally, runs your quality checks, and lands clean data in your warehouse. If a check fails, the pipeline stops — bad data never reaches downstream.

Backfill historical data with --start-date

Schedule with cron or trigger from CI/CD

Full lineage from Notion to your dashboards

$ bruin run .

Running pipeline...

  notion_Tasks
    ✓ Fetched 2,847 new records
    ✓ Quality: campaign_id not_null     PASSED
    ✓ Quality: spend not_null           PASSED
    ✓ Quality: no negative ad spend     PASSED
    ✓ Loaded into bigquery

  Completed in 12s

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Ready to connect Notion?

Start for free, or book a demo to see how Bruin handles ingestion, quality, lineage, and scheduling for your entire data stack.

Book a demo Read the docs