Data & AI Engineer — I design agentic workflows, scalable pipelines, and executive cockpits that turn scattered data into clear decisions.
I am a Data & AI Engineer dedicated to closing the gap between complex data ecosystems and actionable business intelligence. With a background in strategic information monitoring, I bring technical rigor and business strategy to every project.
I specialize in modernizing legacy architectures and pioneering AI-driven initiatives. My work ranges from high-performance Python migrations to the deployment of agentic classification systems using Mistral and GCP.
I focus on building systems that don't just process data, but actively solve organizational bottlenecks through intelligent automation.
My work sits where data engineering meets AI, with a domain focus on retail & payments: acceptance rates, PSP fees, chargebacks, reconciliation, margins by channel.
From raw sources to decisions.
Connecting and modeling data sources into pipelines and KPI cockpits that teams actually use — revenue, margins, payment costs, reconciliation — built on the modern data stack.
LLMs that do real work.
An AI layer on top of business data: agents that answer plain-language questions, classify and route documents, and automate the workflows that eat a team's time.
Domain depth, not just tooling.
A background in the payments industry: the KPIs, edge cases and reconciliation realities behind every transaction — the difference between a generic dashboard and one finance trusts.