Data engineering
Batch and streaming pipelines with schema contracts, retries and lineage you can trace end to end.
Data Services
Data that powers intelligent decisions.
We engineer scalable data infrastructure that transforms complex information into reliable, actionable intelligence.
The problem
Most organisations do not have a data shortage — they have a trust shortage. The same question answered from two systems returns two numbers, pipelines fail quietly overnight, and nobody can say which figure is authoritative. Analysts spend their time reconciling instead of analysing, and every AI initiative downstream inherits the ambiguity.
How we approach it
We start from the decisions the data is meant to support, then design backwards to the models, contracts and pipelines that make those decisions defensible. Every dataset gets an owner, a schema contract and a freshness expectation. Quality checks run as part of the pipeline rather than as a report nobody reads, so a broken upstream change fails loudly at the boundary instead of silently in a dashboard three weeks later.
How it moves
Raw signal to intelligence.
Data is only useful once it is governed, modelled and trusted. This is the path it takes.
Capabilities
What sits inside this practice.
Data integration
Consolidating fragmented sources into one governed layer without freezing the systems that feed it.
Data analytics
Models and metric definitions agreed once, so a number means the same thing in every report.
Data warehousing
Dimensional and lakehouse designs sized for query patterns rather than storage vendor defaults.
Data quality
Validation, anomaly detection and reconciliation running in the pipeline, not after the fact.
Business intelligence
Dashboards built around the decision being made, with the definition behind every figure visible.
Data architecture
Domain boundaries, ownership and access design that survive the next reorganisation.
AI-ready data
Feature stores, embeddings and retrieval sets versioned so model behaviour is reproducible.
Technology
Tools we reach for.
Selected per project against your constraints — never a fixed stack applied by default.
PostgresSnowflakeBigQuerydbtAirflowKafkaSparkDuckDBIcebergGreat ExpectationsMetabasePython
Use cases
Where it applies.
Single source of truth
Retiring the spreadsheet reconciliation that three teams maintain in parallel.
Real-time operations
Streaming telemetry into decisions that have to be made in seconds, not overnight.
Migration off legacy
Moving warehouses without a reporting blackout, running both until the numbers agree.
Foundations for AI
Preparing governed, versioned datasets before a model is trained against them.
Process
How delivery runs.
01 DiscoverDecisions, sources, current pain
02 ArchitectDomains, contracts, ownership
03 IntegrateSources connected and governed
04 TransformModelling and business logic
05 ValidateQuality gates and reconciliation
06 DeliverAnalytics and BI in production
07 ScaleVolume, cost and new domains
Case studies
Selected work.
Structure is content-ready. Real projects appear here once approved for publication.
[PROJECT TITLE]
[CHALLENGE] · [SOLUTION] · [OUTCOME]
[PROJECT TITLE]
[CHALLENGE] · [SOLUTION] · [OUTCOME]
FAQ
Questions we get asked.
You need governed, reproducible datasets. Sometimes that is a warehouse and sometimes it is not — we assess against your query patterns and volumes rather than starting from a product.
Yes. Most engagements begin with systems already in place. We integrate before we recommend replacing anything, and say plainly when replacement is genuinely cheaper.
Checks run inside the pipeline as gates, so a bad upstream change fails at the boundary rather than surfacing as a wrong number in a dashboard weeks later.
Your team. We document domain boundaries and contracts as we go and hand over with the runbooks, rather than leaving knowledge with us.
Build your data foundation.
Bring the reporting you cannot trust, or the AI project waiting on clean inputs. We will map the data you have against the decisions you need and come back with an architecture.