Edu González
Madrid · GMT+1

Edu González — Data & Cloud engineer. I document technical decisions.

I work in Data & Cloud, come from Linux, fullstack, and security, and have spent years learning from the people who built the things we use every day. This blog is where I document what I find.

I write about decisions that official tutorials skip: why this architecture was chosen over that one, what trade-offs were made, what failed in production that nobody documented.

Sometimes the post will answer your question directly. Other times it will give you the uncomfortable answer that forces you to figure it out — because there are no universally correct answers in engineering, only decisions that fit a use case better or worse.

I also publish for fun. I spend weekends exploring things that interest me without a clear goal, like when I started. Those are the posts I enjoy writing most.

Methodology

When I need to solve something, the first question I ask is: has someone already spent years building a validated solution for this? The answer is almost always yes.

Learning to read real production code — understanding why each design decision exists, not just how it works — is what has taught me the most. It requires humility, especially for things that seem trivial.

On AI and the field

We're at an inflection point. AI is automating repetitive technical work at record speed — it's estimated that 46% of GitHub Copilot users' code is generated directly by AI.

The problem is that AI accelerates everything: the good and the bad. A poorly designed architecture will explode much sooner today than five years ago, because adding features is nearly free. Whatever you don't decide, the AI will decide — and AI fills gaps with what's statistically plausible, not what's strategically appropriate.

The value today is in being the person trusted to make technical and strategic decisions — someone who understands the business, understands the technology, and uses AI as their own resource, not as an external consultant delegated the judgment.

How to follow

I'll publish regularly, without calendar promises. I work in consulting, I have a life outside the screen, and I prioritize mental health over forced consistency. What I can guarantee is that when I publish, there will be something concrete to take away.

Subscribe via RSS — no newsletter, no notifications. If you're working on something interesting or want to discuss topics from the blog, write to edunavata@gmail.com . I read everything, though I don't always respond quickly.

Now
2026 — Present
Data Engineer · Álamo Consulting
Financial sector consulting. Working on a large-scale migration of legacy ETL pipelines to Apache Spark for an insurance company, including developing a custom transpiler to automate the conversion.
Apache Spark ETL Data Engineering Python
2024 — 2025
Data Engineer · EDP Renewables
Built and deployed data pipelines end-to-end at an energy company, working solo from architecture to production. First serious engagement with AI as an engineering tool — without delegating architectural judgment.
Cloud Python Data Pipelines
2022 — 2024
Intensive training
Two years in sponge mode: Linux from scratch (Debian), web development, self-hosting, HackTheBox. First open source contribution — landing page for La Velada del Año IV. The goal wasn't to accumulate technologies but to understand how production software really works.
Linux Web Security Open Source
2020 — 2022
Computer Engineering
Bachelor's degree in Computer Engineering. Mathematics and physics nearly drove me out, but programming was immediate. I became obsessed with best practices and "industrial" software before I knew how to build it.
2017 — 2020
First steps
SoloLearn, JavaScript, Python, and Manjaro on an old laptop with a friend. No clear direction, just exploration. Where it all began.
Setup — what I use daily
Editor VS Code + Cursor + kate/nano
Shell zsh + OhMyZsh
Terminal Konsole + Yakuake
OS Fedora KDE
Blog Astro + Tailwind
Hosting Cloudflare Pages GitHub Actions
I write about
Contact
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