Analytics Engineer · Data Products
I design and build production data systems. Pipelines, APIs, models, and interactive products that turn data into decisions.
Before engineering data, I ran a business. That experience shapes every system I build — from understanding the real problem to shipping something that works.
Climate intelligence platform integrating AEMET OpenData and auxiliary sources with scheduled ingestion, FastAPI, and Streamlit monitoring.
Plataforma de inteligencia climática que integra AEMET OpenData y fuentes auxiliares con ingestión programada, FastAPI y monitoreo mediante Streamlit.
Multi-market logistics intelligence with multi-source ETL, operational KPIs, and cost-per-mile modeling on held-out data.
Inteligencia logística multimercado con ETL multifuente, KPIs operativos y modelado de costo por milla sobre datos hold-out.
Web scraping with local AI extraction. URL in, structured JSON out. No API keys. No data leaving your machine.
Web scraping con extracción mediante IA local. Una URL entra, JSON estructurado sale. Sin API keys. Sin datos que salgan de tu máquina.
Domain-agnostic AI decision orchestration platform with human oversight, reliability pipeline, and multi-provider support.
Plataforma de orquestación de decisiones con IA agnóstica al dominio, con supervisión humana, pipeline de fiabilidad y soporte multiproveedor.
raspal (0.6.1, trusted publishing)Map the business context and the decision that needs better information.
Design ingestion, transformation, storage, and access patterns before production code.
Ship pipelines, APIs, and interfaces with tests at every layer and validation at every boundary.
Validate output against the original business problem — not just that it runs.
I ran a business before I built data systems. Managing inventory, costs, logistics, and margins taught me that data is only valuable when it helps someone make a better decision. More about my background →
I'm open to Analytics Engineer opportunities where engineering quality and business context matter.