Architect turned Data Engineer. I build things — in concrete and in code.

I spent years working in construction: pathology diagnostics, structural analysis, full-cycle project design, site supervision. I know what it takes to take something from a blueprint to a standing building. Now I apply that same thinking to data pipelines, automated workflows, and intelligent systems.

The overlap between both worlds is where I do my best work. Buildings generate data. Infrastructure has logic. Design has constraints. I'm interested in the projects that sit at that intersection — digital twins, building automation, smart energy systems, IoT and sensor pipelines, spatial data.

Languages: Python, SQL, JavaScript

Data engineering: dbt, dlt, Kestra, BigQuery, Google Cloud Storage, Terraform

Analysis & tooling: Pandas, Jupyter, Git, REST APIs

Built environment tech: LiDAR scanning, thermal imaging, drone inspections, BIM workflows

The line between a building and a data system is thinner than most people think. Both have inputs, outputs, feedback loops, and failure modes. I'm focused on projects that treat physical infrastructure as a data problem — and on developing the engineering skills to build those systems end to end.

Current focus areas: data engineering, machine learning pipelines, digital twins, building automation, and smart grid analysis.

Smart Meters in London — End-to-End ELT Pipeline A production-grade data pipeline processing ~170 million half-hourly energy consumption records. Built with Terraform, Kestra, dlt, dbt, and BigQuery. Includes CI/CD via GitHub Actions and an interactive Looker Studio dashboard segmenting consumption by weather and socio-economic profile.

Architect by training. Engineer by choice. Building in both directions.