Data engineering
Collecting, transforming and processing data so it can be used reliably. Experience across ETL and distributed processing.
Hello, I'm Enrique
Enrique
Benito Casado.
Data & AI Solution Architect
I'm a computer engineer with a career in data that began in 2011. I bring together hands-on engineering and the broader view of how data platforms are designed.
01 / Professional background
A career built
around data.
My experience connects the detail of building data systems with the decisions that shape them.
I started with reporting, business intelligence and ETL. My work has since grown to include distributed processing, machine learning, Lakehouse platforms and Data & AI architecture.
That progression shapes how I approach technical problems: understanding the wider context while staying close to the engineering. Governance, reliability, observability and cost are part of that thinking.
I keep learning through books, courses and practical exploration, and share part of that process openly on GitHub.
Full career history on LinkedInEducation & continued learning
- Computer Science
- Bachelor's degree
- Big Data Analytics
- Master's degree · Universidad Europea de Madrid
Thesis submitted in 2019 - Databricks Data Engineer Professional
- 2026
Credential details
Listed in my engineering portfolio. A public verification link is not yet available there.
“Think big, start small.”
02 / Expertise
Where I bring
technical depth.
Data engineering and architecture are the core of my work. Machine learning and AI extend the questions I explore.
Data architecture
Designing data models and platforms, understanding trade-offs and connecting technical choices with their operational consequences.
Machine learning & AI
A background in machine learning, with ongoing learning and experimentation in language models and retrieval-augmented generation.
03 / A closer look
Some of what
I build and share.
A few examples of my technical interests and approach. These personal projects and notes complement my professional background.
Engineering portfolio
Databricks & Lakehouse
Engineering patterns, architecture decisions and an ingestion implementation. A closer look at how I think about building reliable data platforms.
What you'll find
Reviewed guides and a locally checked Auto Loader implementation. Execution in a Databricks workspace is still pending.
Master's thesis
Big Data & monitoring
An academic proof of concept following financial news through collection, messaging, storage and monitoring. An end-to-end view of a data architecture.
What you'll find
Research documentation covering Scrapy, Kafka, MongoDB and the Elastic Stack, based on a local virtual-machine environment.
Personal knowledge base
Data architecture notes
The models, patterns and design questions I study. A growing collection that reflects my commitment to understanding and explaining technical ideas.
What you'll find
Personal learning notes on platform architecture, dimensional modeling and Medallion layers, currently being organized and reviewed.
04 / Contact
Let's connect.
To talk about data, exchange ideas or connect professionally,
you can find me on LinkedIn or get in touch by email.