About
I Engineer the Backbone of Data-Driven Decisions.
I’m a junior data engineer with a Master’s degree in Digital Skills for Sustainable Societal Transitions, from Politecnico di Torino, Italy. I enjoy turning messy data into clean, usable structures and building pipelines that make information actually reachable. During my Master’s, I worked on projects that forced me to think critically, take ownership, and deliver solutions under real constraints — not just on paper.
I’m comfortable diving into problems, breaking them down, and figuring out how to move from idea to working implementation. I adapt quickly, work well in fast-moving environments, and collaborate tightly with teams to keep projects on track. My goal is simple: grow into a reliable engineer who builds data tools and workflows that have real impact.

Timeline
Highlights from the last decade.
January 2025 - May 2025
Data Engineering Internship, Politecnico di Torino - Italy
- Designed ETL pipelines to analyze and monitor the academic performance of DAUIN department’s PhD students at Politecnico di Torino.
- Utilized Python for comprehensive data wrangling and transformation, ensuring high-quality, structured datasets ready for downstream analytics.
- Automated the extraction of key employment data by scraping LinkedIn profiles from predefined URLs, leveraging agentic AI tools (Langchain, Ollama and Tavily).
- Built interactive dashboards using Grafana to visualize performance metrics.
- Containerized the entire data pipeline using Docker, ensuring portability, scalability, and ease of deployment across different environments.
July 2022 - September 2022
Quantitative Analyst Internship, MyDigiPay - Iran
- Conducted SQL queries and performed descriptive and inferential statistics analysis on financial data for credit scoring.
- Collaborated with team members to develop machine learning models for classification and regression.
Certificates
Continued learning.
- Apache Spark Essential Training: Big Data EngineeringLinkedIn Learning
- Introduction to LangGraphLangChain Academy
- Introduction to Spark SQL and DataFramesLinkedIn Learning
- Data Engineering with dbtLinkedIn Learning
- Mathematics for Machine Learning: Multivariate CalculusImperial College London, Coursera
- Mathematics for Machine Learning: Linear AlgebraImperial College London, Coursera
- Unsupervised Learning, Recommenders, Reinforcement LearningDeepLearning.AI, Coursera
- Advanced Learning AlgorithmsDeepLearning.AI, Coursera
- Neural Networks and Deep LearningDeepLearning.AI, Coursera
- Supervised Machine Learning: Regression and ClassificationDeepLearning.AI, Coursera
- Data Science Professional CertificateIBM, Coursera
- Data Collection and Processing with PythonUniversity of Michigan, Coursera
- Python Functions, Files, and DictionariesUniversity of Michigan, Coursera
- Python Classes and InheritanceUniversity of Michigan, Coursera
Principles
How I like to work.
Lead with clarity
Every engagement starts with the outcomes, constraints, and signals that matter most.
Ship in loops
Short delivery cycles keep stakeholders engaged and turn complex programs into momentum.
Design for trust
Reliability, observability, and governance get the same attention as shiny new features.
Leave teams stronger
Documentation, pairing, and internal enablement make success sustainable after handoff.
Let's build
Have an initiative that needs momentum?
I'd love to learn about your roadmap, surface opportunities, and co-design a plan that pairs fast delivery with reliable insight.