About
I Engineer the Backbone of Data-Driven Decisions.
I’m a data engineer and data scientist 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.
Nov 2024 - Jan 2026
Data Engineer, DAUIN, 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.
May 2021 - September 2023
Data Engineer, MyDigiPay - Iran
- Managed data integration from multiple sources into the Data warehouse for reporting.
- Resolved ETL bottlenecks, reduced batch job run times, troubleshot and resolved ETL job failures to meet SLAs.
- Implemented Python and SQL-based ETL pipelines orchestrated with Apache Airflow.
- Developed SQL transformations and aggregations powering reporting and analytical tables.
- Prepared datasets and feature tables supporting machine learning models for credit scoring.
- Assisted analysts with curated datasets and ad-hoc data extracts for reporting and exploratory analysis.
- Implemented basic logging, error handling, and retry logic to improve pipeline stability.
- Maintained pipeline documentation and ETL code in Git-based workflows.
Certificates
Continued learning.
DeepLearning.AI Data Engineering Specialization
DeepLearning.AI / Coursera
AWS Certified Cloud Practitioner (CLF-C02) Cert Prep
LinkedIn Learning
Build Data Lakes and Data Warehouses on Google Cloud
Google Cloud / Coursera
Problem-Solving Strategies for Data Engineers
LinkedIn Learning
Apache Spark Essential Training: Big Data Engineering
LinkedIn Learning
Introduction to Spark SQL and DataFrames
LinkedIn Learning
Data Engineering with dbt
LinkedIn Learning
Machine Learning Specialization
DeepLearning.AI
IBM Data Science Specialization
IBM / 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.