Project engineer with experience in Oil&Gas and Shipping Ops, with a master in Data, Data Engineering and AI.
I specialize in building robust data pipelines, training and deploying ML models to production, and automating business processes with Python, Spark and cloud platforms.
"From heavy industry to artificial intelligence: I transform data into decisions."
| Project | Description | Stack |
|---|---|---|
| churn-mlops-databricks | End-to-end MLOps pipeline: ingestion, feature engineering, training & serving on Databricks Delta Lake | Python · PySpark · Databricks · Delta Lake · MLflow |
| fraud-detection-api | Credit card fraud detection with a neural autoencoder (NumPy from scratch) and optimized threshold | Python · NumPy · scikit-learn |
| azure-price-scraper | Azure Functions for web price scraping with HTTP trigger and automated alerts | Python · Azure Functions · requests |
| powerbi-dashboards | Business intelligence dashboards for KPI monitoring with Power BI | Power BI · DAX · SQL |
- Master in Big Data, Data Engineering and AI — ESESA Business School (2025-2026)
- MLOps Essentials: Monitoring Model Drift and Bias — LinkedIn Learning
- Complete Guide to Python Fundamentals for MLOps — LinkedIn Learning
- 42 Málaga — Fundación Telefónica (C, Linux, DevOps)
- LLMOps — Fine-tuning LLMs with Hugging Face PEFT/trl
- Real-Time ML — Streaming with Spark Structured Streaming + Kafka
- ML System Design — Architectural patterns for production
⭐ Open to opportunities in Data roles — Product / LLM / MLOps — Málaga, Spain
