Data Engineering
Data platforms your team can run after we leave
We build and modernise data platforms for AU/NZ organisations, moving teams off brittle pipelines, standing up warehouses that analysts trust, and embedding data quality so problems surface before dashboards lie. We optimise for handover: documented, tested, and recognisably idiomatic in whichever stack you’ve chosen. We don’t resell a single vendor.
What we get hired to build
A few engagement shapes that come up often. Yours probably looks a bit different — that’s fine.
Warehouse migrations done without losing trust
Moving from on-prem SQL Server, legacy Hadoop, or a tangled Redshift to Snowflake, BigQuery, or Databricks. We run old and new in parallel, reconcile row-by-row on the metrics that matter, and cut over only when finance and ops sign off. The number people quote in meetings doesn’t change overnight.
How we engage
Three phases, with explicit decision points. You should be able to walk away after any of them with something useful.
Discovery
We start by framing the problem with the people closest to it. Technical audit of the systems you have, a written risk register for the things that worry us, and a scoped proposal you can compare against doing nothing. Fixed fee, no obligation to continue.
Pilot
A focused build behind a feature flag, kept narrow on purpose. We agree on evaluation criteria upfront, latency, accuracy, cost per run, whatever matters, and there’s an explicit go/no-go conversation at the end. If the pilot doesn’t earn its way to production, we say so.
Production
Phased rollout with monitoring, an on-call runbook, and knowledge transfer to your team. We can stay on a light retainer to evolve the system as your needs change, or hand it over cleanly. Your call.
What we work with
Tooling we reach for by default. Happy to use what your team already runs on.
Have a project that needs to actually ship?
Tell us what you’re trying to do. If we’re not the right fit, we’ll say so and point you somewhere better.
Start a conversation