Services
Backends and APIs built to survive production, plus the deployment that keeps them online.
Pipelines that turn raw operational data into clean, modelled datasets analysts can query.
Dashboards on a modelled warehouse, where the numbers agree and every one can be traced.
Retrieval, structured extraction and evaluation, wired into products that already exist.
Containerised deployment, CI/CD, monitoring and backups — the part that keeps it running.
Selected work
A regional newspaper needed a publishing platform its own editors could run. Client project, live since August 2026 and now operated entirely by their team.
Building an end-to-end analytics platform: ingestion from operational sources, layered transformation in PySpark, and a reporting model analysts query directly. Work carried out within Itransition's commercial data engineering programme.
How we work
First we work out what the system has to do, and just as often, what it must not do.
We start with the data model, because it is the decision hardest to undo later.
We cut the work into pieces that each end in something you can open and look at.
Short cycles, and at the end of each there is something to show.
The system ships in containers, releases are automated, and the way back is written down before anyone needs it.
After that there are two paths: we keep it running, or your team does.
Next step
A short description of the problem is enough to start. You get a written reply with an approach, the rough shape of the work and what it would take. Not a sales call.
