All integrations
Drip
+
Bruin

Drip + Bruin

Source

Ingest Drip 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

  • Marketing impact on revenue

    Join Drip engagement data with CRM deals and payments. Measure what marketing actually drives, not just opens and clicks.

  • Single source of truth

    Combine Drip with all your marketing channels in one warehouse. One dashboard, one set of numbers, no more spreadsheet reconciliation.

  • Clean audience data

    Quality checks catch duplicate contacts, invalid emails, and bounce rate spikes before they affect campaigns.

  • Automated reporting

    Stakeholders get fresh Drip data every morning. No one needs to pull reports or wait for a data team.

For data & engineering teams

How it works

  • Incremental loading

    Only sync new and updated Drip records. No full reloads, no wasted compute, no duplicate contacts.

  • YAML-defined, Git-versioned

    Your Drip pipeline is a YAML file. Review in PRs, deploy with CI/CD, roll back with git revert.

  • Email and contact validation

    Quality checks catch null emails, duplicate contacts, and invalid data before it enters your warehouse.

  • Cross-source dependency resolution

    Bruin resolves dependencies between Drip and other sources automatically. Transforms run in the right order.

Before you start

API key from Drip user settings
Account ID from Drip general settings

Step 1

Add your Drip connection

Connect using API key and account ID. Add this to your Bruin environment file — credentials are stored securely and referenced by name in your pipeline YAML.

Parameters

  • api_keyAPI key from Drip settings
  • account_idDrip account ID
connections:
  drip:
    type: drip
    uri: "drip://?api_key=<api-key>&account_id=<account-id>"

Step 2

Create your pipeline

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

Available tables

subscriberscampaignsworkflowseventstags
name: raw.drip_subscribers
type: ingestr

parameters:
  source_connection: drip
  source_table: 'subscribers'
  destination: bigquery

Step 3

Add quality checks

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

Catch duplicate contacts before they enter your warehouse
Validate email fields are never null
Ensure record IDs are unique across syncs
columns:
  - name: id
    checks:
      - name: not_null
      - name: unique
  - name: email
    checks:
      - name: not_null

custom_checks:
  - name: no duplicate contacts
    query: |
      SELECT COUNT(*) = COUNT(DISTINCT email)
      FROM raw.drip_subscribers

Step 4

Run it

One command. Bruin connects to Drip, 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 Drip to your dashboards
$ bruin run .
Running pipeline...

  drip_subscribers
    ✓ 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

Ready to connect Drip?

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