Marketo + Bruin

Source

Ingest Marketo 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 Marketo engagement data with CRM deals and payments. Measure what marketing actually drives, not just opens and clicks.
Single source of truth
Combine Marketo 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 Marketo 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 Marketo records. No full reloads, no wasted compute, no duplicate contacts.
YAML-defined, Git-versioned
Your Marketo 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 Marketo and other sources automatically. Transforms run in the right order.

Before you start

Marketo account with API access

LaunchPoint service created for API

Admin permissions to generate credentials

Step 1

Add your Marketo connection

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

Parameters

client_idMarketo API client ID
client_secretMarketo API client secret
munchkin_idMarketo Munchkin account ID

connections:
  marketo:
    type: marketo
    uri: "marketo://client_id:client_secret@munchkin_id"

Step 2

Create your pipeline

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

Available tables

leadsactivitiescampaignsprogramslistsopportunities

name: raw.marketo_leads
type: ingestr

parameters:
  source_connection: marketo
  source_table: 'leads'
  destination: bigquery

Step 3

Add quality checks

Add column-level and custom SQL checks to your Marketo 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.marketo_leads

Step 4

Run it

One command. Bruin connects to Marketo, 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 Marketo to your dashboards

$ bruin run .

Running pipeline...

  marketo_leads
    ✓ 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

Other Marketing integrations

ActiveCampaign

Adjust

AdMob

AdRoll

Amazon Ads

Amplitude

Ready to connect Marketo?

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