Twilio + Bruin
Ingest Twilio 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 Twilio engagement data with CRM deals and payments. Measure what marketing actually drives, not just opens and clicks.
Single source of truth
Combine Twilio 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 Twilio 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 Twilio records. No full reloads, no wasted compute, no duplicate contacts.
YAML-defined, Git-versioned
Your Twilio 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 Twilio and other sources automatically. Transforms run in the right order.
Before you start
Step 1
Add your Twilio connection
Connect using Twilio account credentials. Add this to your Bruin environment file — credentials are stored securely and referenced by name in your pipeline YAML.
Parameters
account_sidTwilio Account SIDauth_tokenTwilio Auth Token
connections:
twilio:
type: twilio
uri: "twilio://account_sid:auth_token"Step 2
Create your pipeline
Define a YAML asset that tells Bruin what to pull from Twilio and where to land it. This file lives in your Git repo — reviewable, version-controlled, and deployable with CI/CD.
Available tables
name: raw.twilio_messages
type: ingestr
parameters:
source_connection: twilio
source_table: 'messages'
destination: bigqueryStep 3
Add quality checks
Add column-level and custom SQL checks to your Twilio data. If a check fails, the pipeline stops — bad data never reaches downstream models or dashboards.
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.twilio_messagesStep 4
Run it
One command. Bruin connects to Twilio, 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.
--start-date$ bruin run .Running pipeline...
twilio_messages
✓ 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 12sOther Marketing integrations
Ready to connect Twilio?
Start for free, or book a demo to see how Bruin handles ingestion, quality, lineage, and scheduling for your entire data stack.


