Microsoft data engineering
Power your business with bold, modern data engineering.
In a world where data never sleeps, modern engineering matters. Legacy limitations and slow insights hold businesses back, but your data strategy can’t afford to stand still.
We bring scalable Microsoft expertise across Fabric, Azure Databricks, GitHub and DevOps to transform how you build and optimise platforms. From Real-Time Intelligence in Fabric to Spark Structured Streaming and Lakeflow Declarative Pipelines in Databricks, we help you surface hidden value and futureproof operations.
Outcomes arrive early, not eventually – because engineering should deliver impact from day one.
We don’t believe in waterfall thinking.
Instead, we drive a use-case-first approach – breaking down complexity and delivering meaningful outcomes, fast. Our teams prioritise quick wins that generate business value from day one, not month twelve. It’s about getting more from your investment before the project even finishes.
By aligning our engineering sprints to your specific business challenges, we help you gain traction where it matters most. Whether it’s streamlining operational workflows, enabling real-time decisions, or cutting costs through smarter architectures – our approach is designed to deliver value early and often.
Real clients. Real results.
Explore our case studies to see how we’ve delivered strategies and solutions across industries – tackling challenges, enabling transformation, and proving what’s possible when it’s data by design.
Data Architecture: Designed a scalable Databricks platform with Bronze, Silver, and Gold layers - improving trust, access, and enabling faster, real-time business decisions.
Data Strategy: Delivered updated IP & I data strategy and roadmap, closing audits, reducing risk, and meeting client expectations within agreed timelines and budget.
Data Analytics & Reporting: Built data mart and dashboards, enabling 70,000+ business switches, improving campaign optimisation, and meeting regulatory compliance requirements
Your Questions, Answered.
Why do I need DevOps in data engineering?
DevOps and CI/CD brings control. It provides change management, rollback capability, and governance, making your engineering lifecycle more reliable, faster, and future-ready.
Fabric vs. Databricks – which is right?
It depends. Team capability, tools, and maturity all play a part. We help you assess what fits best.
How do GitHub and DevOps fit into Microsoft Data Engineering?
GitHub and Azure DevOps bring automation, version control, and collaboration to data engineering. By combining them with Microsoft Fabric and Azure Databricks, we ensure pipelines are secure, governed, and continuously optimised. This means faster delivery, fewer errors, and a more agile platform – built for AI, analytics, and future innovation.
Ben Woodhouse
Isobel Daley
Lalith Korae
Megan Livadas
Oliver Saywell
Fraser Black
Jonathon Moore
All set to make your data AI-ready?
In one conversation, we’ll explore your challenges, share ideas, and leave you with clear next steps – questions to spark internal discussions and practical ways to progress your data and AI journey with confidence.
Let’s talk
Victoria Whittaker
Head of Business Development