Summary
Nicola De Lillo is a data engineer with 12 years of experience who moved from gravitational-wave astronomy into building production ETL/ELT pipelines using Python, SQL, dbt, PySpark and AWS/Databricks. He has led data warehouse design, DAG orchestration (Dagster), and delivery of 20+ business reports while embedding data quality and governance practices across organizations. Nicola’s academic background includes hands-on Bayesian inference and parameter estimation for landmark neutron star–black hole detections, bringing rigorous scientific modeling and reproducible research habits to engineering teams. He combines research-grade numerical simulation and instrumentation experience with pragmatic cloud-native engineering, and has supported cross-disciplinary projects linking physical activity research to business KPIs. Based in Italy, he’s actively studying machine learning and AI to bridge advanced analytics with scalable data platforms.
12 years of coding experience
6 years of employment as a software developer
Master's degree, Physics, Master's degree, Physics at Università di Trento
Doctor of Philosophy - PhD (Not completed), Astronomy and Astrophysics, Doctor of Philosophy - PhD (Not completed), Astronomy and Astrophysics at University of Glasgow