Technical perspectives on cloud infrastructure, modern data platforms, and the architecture decisions that matter — plus hypothetical case studies that show how the work could play out for a real team.
The case studies on this site are personal examples built for hypothetical companies. They are not records of paid client engagements. Each one is a worked-through scenario showing how data engineering decisions — warehouse choice, pipeline design, governance, attribution — could be applied for a realistic D2C, SaaS, or regulated business. Treat them as illustrative architecture write-ups, not testimonials.
How we architected a data platform for a UK health-tech company that processes sensitive patient data — balancing analytical power with UK GDPR compliance, data minimisation, and auditability across every layer of the stack.
An end-to-end data architecture built with AWS, Snowflake, and dbt, structured around the medallion architecture — moving data from raw ingestion to trusted, business-ready outputs in a way that is secure, maintainable, and ready to scale.
How we built a robust, real-time data lakehouse on Azure and Databricks — streaming ingestion, CDC, AI-powered sentiment analysis, and Medallion Architecture delivering 12x faster processing and up to 97% lower TCO.
A technical comparison of object, block, file, and analytical storage across the three major cloud providers — when to use each, and the trade-offs that matter.
How we designed and delivered a real-time inventory data platform for a UK retailer operating 45 stores and an e-commerce channel — eliminating stockouts, reducing overstock by 32%, and enabling same-day fulfilment decisions.
How we helped a UK fintech replace a fragile, manually-maintained ETL pipeline with an automated, tested, and observable modern data stack — reducing data incidents by 94% and cutting pipeline maintenance from 20 hours/week to under 2.
A 30-minute conversation to understand your stack, your attribution gaps, and whether our approach makes sense. No pitch deck. No commitment.