- Role: Data & Machine Learning Engineer.
- Focus: Designing resilient, scalable data architectures and deploying ML models.
- System Design: Passionate about distributed systems; avid reader of Designing Data-Intensive Applications and Software Architecture: The Hard Parts.
- Certifications: Databricks (Professional & Associate), AWS (ML Specialty), Google Cloud (Pro ML Engineer), Neo4j Professional.
- Education: MSc in Computer Science (108/110) from University of Milan.
- Achievements: Winner of the NASA Space Apps Challenge 2025 (Zurich local competition).
- Interests: Rock climbing, Board games, PC gaming, and Competitive Programming.
| Category | Technologies |
|---|---|
| Languages |    |
| Cloud |    |
| Data Eng |      |
| ML & AI |     |
| DevOps |     |
May 2024 – Present
- Enterprise-Scale Data Pipelines & Historical Data Optimization: Designed high-volume data ingestion pipelines (Databricks, Medallion Architecture) for Prada; optimized historical tracking with SCD Type 2, reducing query time by 80%.
- Optimized Data Orchestration: Migrated Airflow DAGs to GCP Composer 2.x, boosting scheduling efficiency by 10x for Becko.
- Sanctioned Shop Blocker: Optimized sanctions-screening lakeflow job for customer onboarding; significantly improved performance and reduced data size to a quarter.
- CI/CD: Established CI/CD pipelines in Azure DevOps and GitHub Actions to automate code testing with pytest and Databricks Asset Bundles.
- RAG-powered CloudFormation Template Generator: Developed a UI-driven tool to generate AWS CloudFormation templates from natural language. The engine retrieves AWS formatting documentation to guarantee a well-written YAML output.
- ETL Refactoring: Optimized IBM DataStage workflows and SQL for banking data warehouses.
| Project | Description | Stack |
|---|---|---|
| NASA Space Apps Challenge 2025 | Team Leader & Dev for the winning solution at the Zurich local competition. | Python Data Analysis |
| BoardGames RAG | AI system for interacting with board game rules via natural language. | RAG LLMs Vector DB |
| QueryScorer | CI pipeline tool ensuring only optimized SQL queries are committed. | CI/CD SQL Python |
| AlphaEvolveTryout | Simplified AlphaEvolve implementation to study evolutionary algorithms. | Python Algorithms |