Stop arguing about dashboards
A pipeline that works 99% of the time is a pipeline that lies to you the other 1% — usually before the board meeting. Our data engineering standard treats every pipeline like production software: tested, monitored, and boring in the best way.
What we build
- ETL / ELT pipelines — batch and incremental jobs moving data from your apps and tools into one clean, documented place.
- Data warehouses & modelling — Snowflake, BigQuery or Postgres with dbt-style models: customers_360, revenue, churn.
- Streaming & real-time — Kafka pipelines for live dashboards and fraud checks, when yesterday’s data is too late.
- BI, dashboards & governance — dashboards people actually open, plus access control, lineage and data-quality monitors.
How we guarantee reliability
- Tests on the data itself — freshness, volume and value checks on every load; bad data quarantines, never ships.
- Observability built in — run history, lineage and alerts before go-live, not after the first incident.
- Idempotent by design — re-run any job safely; backfills are routine, not emergencies.
- Documented models — every table has an owner, a definition and a freshness SLA.
- Your cloud, your keys — everything runs in your accounts with infrastructure-as-code you own.
How much does a data pipeline cost?
A production pipeline with tests and monitoring starts around NZ$15,000; warehouse and modelling engagements scale with scope. We start with your most painful report so the business feels the difference before the engagement ends. Diagnose your data — we’ll tell you what’s likely wrong for free.