I'm a data engineer with seven years of experience building data solutions in financial services. My background spans both sides of the industry - from data provision at Bloomberg to data consumption at Mercer.

At Bloomberg Fixed Income Data, I focused on data modeling, quality assurance, and maintaining pipelines that fed their terminal services. I spent my time cleaning data, analyzing trends, and writing technical documentation.

At Mercer, I transitioned into full-stack data engineering. I built financial reporting systems from scratch using dbt, Python and PostgreSQL. My work supported pension analytics and investment reporting for their consulting teams.

I enjoy solving complex data problems and translating business requirements into reliable technical solutions. Having worked on both the provider and consumer sides gives me a practical understanding of how data systems need to perform in enterprise environments.

This blog covers the most interesting projects I've worked on - from building data pipelines and designing databases to creating dashboards and reports. I'll share real examples of how I've used programming, SQL, and business intelligence tools to solve actual business problems.

I'm currently fascinated with Go. It's an incredibly fast, functional language that compiles quickly and handles concurrency beautifully. Coming from Python, I'm impressed by how Go balances simplicity with performance - perfect for data processing applications.

I'm probably hiking somewhere. There's something about being outdoors that helps clear my head after spending hours debugging SQL queries.