Data Engineering

The Data Foundation AI Requires

AI is only as good as the data feeding it. We architect and build the data infrastructure that makes machine learning reliable, analytics trustworthy, and reporting instant — on modern Azure data platforms.

Bad data in, bad AI out

Most AI projects fail not because of the model — but because of the data. Siloed databases, inconsistent schemas, untested pipelines, and missing governance mean AI systems produce unreliable outputs that erode trust.

We audit your current data landscape, identify the gaps, and build the infrastructure that makes both BI and AI work reliably. Whether that's migrating from legacy on-premise systems or scaling your existing Azure setup.

Unified data platform — one source of truth across all systems
Azure-native architecture with Microsoft Fabric integration
GDPR-compliant storage and processing by design
Automated quality checks on every pipeline
Full data lineage — trace any metric back to its source

Common data challenges we fix

Data siloed across 10+ systems
Unified data lake with automated ingestion
Pipelines break without warning
Monitored pipelines with automatic alerting
Nobody trusts the numbers
Data quality framework with lineage tracking
Reports take days to produce
Real-time analytics layer on Azure Synapse

Data engineering services

Azure Data Platform Architecture

End-to-end design and implementation of modern data platforms on Azure — Data Lake, Synapse Analytics, Databricks — built to scale with your business.

ETL / ELT Pipeline Development

Robust, tested, and monitored data pipelines using Azure Data Factory, dbt, and Apache Spark — turning raw source data into clean, analytics-ready datasets.

Real-Time Streaming

Event-driven data architectures with Azure Event Hubs and Azure Stream Analytics — processing millions of events per second for operational analytics use cases.

Data Warehouse & Lakehouse

Design and build structured analytical stores optimised for BI tools and AI workloads — combining the flexibility of data lakes with the performance of warehouses.

Data Quality & Governance

Automated data quality checks, lineage tracking, and cataloguing with Microsoft Purview — so you always know what data you have, where it came from, and whether to trust it.

Legacy Migration to Azure

Migrate on-premise databases, ETL processes, and reporting infrastructure to Azure — with zero-downtime migration strategies and parallel run validation.

Azure-native data stack

We build on Microsoft Azure data services — maximising your existing Azure investment and keeping everything within Europe.

Azure Data FactoryAzure DatabricksAzure Synapse AnalyticsAzure Data Lake Storage Gen2Azure Event HubsAzure Stream AnalyticsMicrosoft FabricMicrosoft PurviewAzure SQL / Managed Instancedbt (data build tool)Apache SparkApache Kafka

Let's audit your data infrastructure

A free 1-hour data architecture review. We'll identify your biggest blockers and prioritise what to fix first.

Book a Data Architecture Review