Data engineering that turns scattered, messy data into a foundation you can build on.
Most data engineering and platforms services stop at a working pipeline and call it done. Ours is built as the platform your data products, BI and machine learning actually run on — data driven product development handled end to end by senior data product developers, with a first reliable pipeline usually live in 6 weeks.
The problems that bring
teams to us to build a data platform.
If any of these sound familiar, it's usually a sign your data has outgrown ad hoc exports and spreadsheets — here's how we approach it.
Data scattered across a dozen systems
Every team has its own export, its own spreadsheet, its own version of the truth — and none of them quite agree.
No governance, so nobody trusts the numbers
Without clear ownership and data quality rules, every dashboard gets a “is this even right?” before anyone acts on it.
Pipelines that break the moment volume grows
What ran fine against a sample dataset falls over the first time it meets real production volume.
BI and ML stuck waiting on manual prep
Your analysts and data scientists spend more time wrangling data than actually using it.
A data platform,
not just a pipeline.
Most data engineering services stop at moving data from A to B. Ours starts with what B needs to support next — dashboards, models, and the data products your business hasn't built yet — so you're not re-engineering the foundation every time a new use case shows up.
Good data engineering is invisible when it works.
Nobody notices a pipeline that runs on time with clean, governed data behind it — they only notice when it breaks or the numbers don't add up. We build the boring, reliable foundation so your BI and ML teams can focus on insight, not data wrangling.
Built as a platform, not a one-off pipeline
Every pipeline, warehouse and dataset is designed to support the next data product, not just the one you asked for first.
Governed and documented from day one
Data quality, lineage and access control built in, so the answer to “can we trust this number” is always yes.
AI-accelerated, senior-led build
AI-assisted tooling handles the boilerplate so senior data engineers spend their time on the architecture decisions that actually matter.
The same team ships the BI and ML on top
No handoff between the people who build the pipeline and the people who build what runs on it.
A working method, not a deck of phases.
Discover
We get into the detail. Stakeholders, constraints, data, and the real problem you're trying to solve.
Strategise
We sketch the smallest version that proves the outcome. A clear plan, a tight scope, no fluff.
Build
Cross-functional pods of engineers, designers, and data folk. Working software every week.
Scale
We harden it, instrument it, and stick around. Roadmaps, reviews, and a team that knows your stack.
Not sure if you need a pipeline, a dashboard or a model? Ask the engineer who’d build it.
Book a 30-minute working session with a senior data engineer — a real conversation about your data, not a sales call.
Built with clients
who measure outcomes.
A 12-tab spreadsheet, rebuilt as a risk platform
Offshore cable burial risk assessment taken out of a straining Excel workbook and rebuilt as a Python engine and React application on Microsoft Azure — a hundred thousand rows of AIS vessel data, Carbon Trust anchor-strike methodology, and depth-of-lowering curves for every soil zone on a route.
Frasers Aerospace — Operations Control Tower
An operations dashboard for an AS9120B aerospace supplier, built in Microsoft Lists and Power BI — orders from Sage 200 and WooCommerce in one place, the spreadsheets they used to be raised in retired, the exceptions blocking them surfaced first, and a TV wallboard for the warehouse floor.
“Most data problems aren’t a modelling problem, they’re a plumbing problem. Fix the pipeline and the governance first, and the dashboard your team actually wanted becomes the easy part.”
Sectors we've built data platforms for.
We've designed and shipped data engineering for teams across every one of these sectors.
The stack we ship on.
Pragmatic, mostly boring, and chosen because it works in production — not because it's on the front page of Hacker News.
Pipelines & orchestration
- Airflow
- dbt
- Databricks
Warehousing & storage
- Snowflake
- BigQuery
- Redshift
AI-accelerated build
- Claude
- Cursor
- GitHub Copilot
Oliver's adept project management skills were evident as he consistently delivered all projects within set timelines.Read more client stories
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Data engineering services,
and what we build on them.
Data engineering
We design and build the data infrastructure that powers intelligent decision-making — from ingestion to insight.
Learn moreData products
Standalone data products your team can actually use.
Learn more 02Data solutions
Bespoke solutions to your most complex data challenges.
Learn more 03BI & analytics
Dashboards and reporting tools that turn raw data into clear decisions.
Learn more 04Machine learning & MLOps
Predictive models and ML pipelines designed for production.
Learn more 05Data consultancy
Strategic advice on how to structure, govern, and get more value from your data.
Learn moreQuestions, answered straight.
Have an outcome in mind?
We'll help you
ship it.
- You're building a data product and need a team that can deliver.
- You want to get AI-ready — pragmatically, not theoretically.
- Your reporting is a mess and you need a real platform underneath it.