All integrations
PayPal
+
Bruin

PayPal + Bruin

Source

Ingest PayPal 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

    PayPal transaction data flows into your warehouse with quality checks that validate amounts, currencies, and reconciliation — every single sync.

  • MRR/ARR calculated right

    Combine PayPal 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 PayPal 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 PayPal transactions are never duplicated, even on retry.

  • YAML-defined, Git-versioned

    Your PayPal 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 PayPal data in BigQuery, Snowflake, Redshift, or DuckDB. Switch destinations by changing one line.

Before you start

PayPal Business account
REST API app created in Developer Dashboard
Client ID and secret from app credentials

Step 1

Add your PayPal connection

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

Parameters

  • client_idPayPal REST API client ID
  • client_secretPayPal REST API client secret
  • merchant_idPayPal merchant account ID
connections:
  paypal:
    type: paypal
    uri: "paypal://client_id:client_secret@merchant_id"

Step 2

Create your pipeline

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

Available tables

transactionspaymentspayoutsdisputesinvoicessubscriptions
name: raw.paypal_transactions
type: ingestr

parameters:
  source_connection: paypal
  source_table: 'transactions'
  destination: bigquery

# Syncs transactions, invoices, and payment
# data with idempotent incremental loads.

Step 3

Add quality checks

Validate PayPal data on every sync. Catch amount mismatches, missing currencies, and reconciliation failures before they reach finance reports.

Validate that credits and debits balance
Catch null amounts and missing currencies
Ensure transaction IDs are unique — no duplicates
columns:
  - name: 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(CASE WHEN type = 'credit'
        THEN amount ELSE -amount END)) < 0.01
      FROM raw.paypal_transactions
      WHERE created_at > CURRENT_DATE - 1

Step 4

Run it

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

  paypal_transactions
    ✓ 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

Ready to connect PayPal?

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