Build the data foundation your business can trust
We design and deliver scalable pipelines, warehouses and transformations on Microsoft technologies, so your teams work from one reliable source of truth.
Explore subservicesPrepare, centralise and transform your data for activation
From first ingestion through governed storage to analytics-ready models, our data engineering consulting works alongside your team to connect every layer to outcomes you can measure.
Why this matters
Most growing companies are held back by disconnected data - hundreds of apps, hours lost searching for answers, and teams deciding in silos.
Industry research
Software applications in large organisations
29% of work week
Per week wasted searching for data
Of teams operate in silos
Source: Forrester Consulting "Crisis of a fractured organization" study of 1,022 U.S. and U.K. workers, 2024
Explore our data engineering capabilities
Select a capability to see how we deliver it on Microsoft Fabric and Azure.
Build and implement scalable, efficient data pipelines that bring data from every source into your Microsoft platform: automated, monitored and ready for downstream use.
What we do
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Data landscape audit
Gain clear insight into your existing sources, connectors and ingestion flows. We map a practical path to reliable, automated pipelines.
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Pipeline design and build
We implement ELT/ETL flows on Azure Data Factory and Microsoft Fabric Data Factory, connecting SaaS, databases and files with repeatable patterns.
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Monitoring and operations
Establish alerting, lineage awareness and runbooks so ingestion stays healthy without constant firefighting from your team.
Ensure data is reliable, high-quality and analytics-ready. We apply business rules, modelling and quality checks so activation happens with confidence.
What we do
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Transformation and modelling
Define layered models and transformation logic that reflect how your business actually works: documented, testable and maintainable.
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Data quality and governance
Embed validation, reconciliation and ownership so stakeholders trust the numbers before they reach dashboards or AI workloads.
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Analytics-ready datasets
Deliver curated tables and semantic-ready structures that Power BI and Fabric can consume without rework.
Remove silos by centralising data in a governed warehouse or lakehouse. One platform for analytics, self-service and AI, with consistent access and security.
What we do
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Architecture workshop
Design a future-ready foundation on Microsoft Fabric and OneLake, aligned to your sources, security model and analytics ambitions.
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Lakehouse and warehouse build
Implement medallion or dimensional structures with clear zones for raw, refined and curated data your teams can navigate.
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Governed access and enablement
Configure workspaces, roles and patterns for self-service so the right people reach the right data without IT bottlenecks.
Built on Microsoft
We implement on the platforms your organisation already trusts.
Microsoft Fabric 
Power BI 
Azure 
Azure Databricks 
Microsoft Copilot 
SQL Server Engineering principles that keep foundations dependable
Data platforms fail quietly: a broken refresh here, an undocumented pipeline there. Our ways of working are built to prevent that.
Always together
Your IT and data people stay in every design decision, from source access to warehouse layers, so the platform is one your team can operate, not a black box we hand over.
Think big, start small
We map the target architecture first, then deliver one trusted pipeline or domain at a time - each increment goes to production and proves its value before the next begins.
Build modular
Ingestion, transformation and storage are built as separable blocks with clear contracts, so swapping a source or adding a domain later does not mean rebuilding the platform.
Common questions about data engineering
What teams ask before building or modernising their data foundation on Microsoft.
Do you replace our existing data platform?
Not by default. We assess your sources, architecture and constraints, then modernise in blocks on Microsoft Fabric, Azure or the hybrid path that fits your reality. The goal is a foundation you can extend, not a rip-and-replace programme unless that is what the business needs.
How do you make sure teams trust the data?
We define ownership, quality checks, reconciliations and lineage before analytics or AI activation. Clear metric definitions and documented transformation logic mean stakeholders can explain the numbers behind every dashboard.
How long until we have a usable foundation?
Many engagements deliver a first trusted pipeline and curated datasets within weeks, depending on scope and source complexity. We think big, start small: early wins build momentum while the broader architecture takes shape in blocks.
Do you work with hybrid or legacy systems?
Yes. We integrate SaaS, on-premises databases, files and existing Azure or Fabric estates. The goal is a practical path forward on Microsoft technologies, not a forced migration away from systems that still serve the business.
Let's build your analytics future
Every great decision starts with great data. Tell us where you are today and we'll map the fastest path forward.