FreshBooks + Bruin

Source

Ingest FreshBooks 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

Revenue reporting you can audit
FreshBooks transaction data flows into your warehouse with quality checks that validate amounts, currencies, and reconciliation, every single sync.
MRR/ARR calculated right
Combine FreshBooks with subscription data to automate MRR, ARR, and churn calculations. Finance gets numbers, not guesswork.
Catch issues before close
Quality checks flag missing transactions, amount mismatches, and anomalies. Finance finds out from Bruin, not from the CFO.
Unified financial view
Join FreshBooks with your ERP, CRM, and other financial tools. One source of truth for revenue, not five spreadsheets.

For data & engineering teams

How it works

Idempotent incremental loads
Re-runs are safe. Bruin's merge strategy ensures FreshBooks transactions are never duplicated, even on retry.
YAML-defined, Git-versioned
Your FreshBooks pipeline is a YAML file. Review in PRs, deploy with CI/CD, roll back with git revert. Auditors love this.
Reconciliation checks
Custom SQL checks validate that amounts balance and currencies match. Pipeline stops if something doesn't add up.
Multi-destination support
Land FreshBooks data in BigQuery, Snowflake, Redshift, or DuckDB. Switch destinations by changing one line.

Before you start

FreshBooks account with API app registered in developer portal

Step 1

Add your FreshBooks connection

Connect using FreshBooks OAuth2 credentials. Add this to your Bruin environment file, credentials are stored securely and referenced by name in your pipeline YAML.

Parameters

client_idFreshBooks OAuth2 client ID from developer portal
client_secretFreshBooks OAuth2 client secret
refresh_tokenOAuth2 refresh token from authorization flow
account_idYour FreshBooks account or business ID

connections:
  freshbooks:
    type: freshbooks
    uri: "freshbooks://?client_id=<your-client-id>&client_secret=<your-client-secret>&refresh_token=<your-refresh-token>&account_id=<your-account-id>"

Step 2

Create your pipeline

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

Available tables

invoicesclientsexpensespaymentsprojects

name: raw.freshbooks_invoices
type: ingestr

parameters:
  source_connection: freshbooks
  source_table: 'invoices'
  destination: bigquery

Step 3

Add quality checks

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

Validate that credits and debits balance

Catch null amounts and missing currencies

Ensure transaction IDs are unique, no duplicates

columns:
  - name: transaction_id
    checks:
      - name: not_null
      - name: unique
  - name: amount
    checks:
      - name: not_null
  - name: currency
    checks:
      - name: not_null

custom_checks:
  - name: amounts balance
    query: |
      SELECT ABS(SUM(credit) - SUM(debit)) < 0.01
      FROM raw.freshbooks_invoices

Step 4

Run it

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

$ bruin run .

Running pipeline...

  freshbooks_invoices
    ✓ 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 Payments & Finance integrations

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Ready to connect FreshBooks?

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