About

I'm an analytics engineer with a privacy-first mindset, an early adopter of AI tooling, and a self-hoster by conviction. I build data pipelines for a living and document my learning journey on this site.

What I do

I've spent the last four-ish years deep in data engineering - building production dbt repositories from scratch, writing and optimizing SQL on Redshift, and setting up CI/CD pipelines that the rest of the team relies on.

The work I enjoy most is the kind with a measurable result: taking a model that runs in 3000 seconds and getting it down to 100. Building a CI/CD pipeline from zero that saves minutes per deployment. Creating internal APIs and tools that make my team's life easier.

I operate across the full stack of my domain - from SQL and data modeling, through Python scripting and API development, to Docker containers, GitLab pipelines, and infrastructure. Not just "someone who writes queries."

I'm always happy to pick up work that stretches past what I already know - often requests that come in from other teams - because that's how I pick up skills that eventually feed back into analytics engineering.

How I think about work

Privacy-first

This isn't a marketing angle. I de-Google my own life, run a homelab instead of relying on cloud services, manage my network through a Mikrotik with Pi-hole, and host my own media on Jellyfin. When I work with data, I naturally think about where it goes and who has access - not because a compliance checklist tells me to, but because that's how I'm wired.

AI-augmented

I use Cursor daily to build dbt infrastructure - rules, skills, automated model generation. I've integrated with the Gemini API for batch processing pipelines. My approach is pragmatic: what does AI actually make better vs. what's just a shiny gadget?

Independence and ownership

Side projects and this site run on my own priorities and cadence. At work I still aim to see the whole picture - not just the patch I'm assigned. I enjoy turning dense technical detail into something non-engineers can use; explaining it clearly is how I check that I really get it.

Tech stack

Beyond work

When I'm not building pipelines or tinkering with my homelab, I'm probably running (training for a 5K) or gaming - often both in the same evening.