Wise + Bruin
Ingest Wise 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
Wise transaction data flows into your warehouse with quality checks that validate amounts, currencies, and reconciliation — every single sync.
MRR/ARR calculated right
Combine Wise 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 Wise 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 Wise transactions are never duplicated, even on retry.
YAML-defined, Git-versioned
Your Wise 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 Wise data in BigQuery, Snowflake, Redshift, or DuckDB. Switch destinations by changing one line.
Before you start
Step 1
Add your Wise connection
Connect using Wise API credentials. Add this to your Bruin environment file — credentials are stored securely and referenced by name in your pipeline YAML.
Parameters
api_keyWise API tokenprofile_idWise profile IDenvironmentEnvironment: live or sandbox (default: live)
connections:
wise:
type: wise
uri: "wise://?api_key=<api_key>&profile_id=<profile_id>&environment=<environment>"Step 2
Create your pipeline
Define a YAML asset that tells Bruin what to pull from Wise and where to land it. This file lives in your Git repo — reviewable, version-controlled, and deployable with CI/CD.
Available tables
name: raw.wise_transfers
type: ingestr
parameters:
source_connection: wise
source_table: 'transfers'
destination: bigqueryStep 3
Add quality checks
Add column-level and custom SQL checks to your Wise data. If a check fails, the pipeline stops — bad data never reaches downstream models or dashboards.
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.wise_transfersStep 4
Run it
One command. Bruin connects to Wise, 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...
wise_transfers
✓ 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 Wise?
Start for free, or book a demo to see how Bruin handles ingestion, quality, lineage, and scheduling for your entire data stack.