Calendly + Bruin
Ingest Calendly 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
Calendly data in your warehouse means analytics that Calendly's built-in reporting can't provide. Cross-tool, cross-team, custom.
Cross-tool project views
Combine Calendly 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 Calendly data — automatically updated.
No manual data pulling
Calendly 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 Calendly records. No full reloads, no wasted compute.
YAML-defined, Git-versioned
Your Calendly pipeline is a YAML file. Review in PRs, deploy with CI/CD, roll back with git revert.
Schema change handling
Bruin detects Calendly schema changes automatically. No manual intervention when fields get added or renamed.
Cross-tool joins
Combine Calendly data with other tools in SQL transforms. Bruin resolves dependencies across sources automatically.
Before you start
Step 1
Add your Calendly connection
Connect using Calendly personal access token. Add this to your Bruin environment file — credentials are stored securely and referenced by name in your pipeline YAML.
Parameters
api_keyCalendly personal access token from Integrations settings
connections:
calendly:
type: calendly
uri: "calendly://?api_key=<your-personal-access-token>"Step 2
Create your pipeline
Define a YAML asset that tells Bruin what to pull from Calendly and where to land it. This file lives in your Git repo — reviewable, version-controlled, and deployable with CI/CD.
Available tables
name: raw.calendly_events
type: ingestr
parameters:
source_connection: calendly
source_table: 'events'
destination: bigqueryStep 3
Add quality checks
Add column-level and custom SQL checks to your Calendly 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: title
checks:
- name: not_null
custom_checks:
- name: workspace sync is complete
query: |
SELECT COUNT(*) > 0
FROM raw.calendly_eventsStep 4
Run it
One command. Bruin connects to Calendly, 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...
calendly_events
✓ 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 12sReady to connect Calendly?
Start for free, or book a demo to see how Bruin handles ingestion, quality, lineage, and scheduling for your entire data stack.