
I am a seasoned data engineer and cloud architect with extensive experience designing and leading modern data platforms across multiple industries, including finance, insurance, and automotive. With a Master’s degree in Computer Science Engineering from Alma Mater Studiorum - Università di Bologna, I have honed strong problem-solving and teamwork skills alongside deep technical expertise in big data technologies such as Apache Spark, Kafka, and cloud platforms including GCP, Azure, and AWS. I have successfully led large-scale migrations of legacy systems to scalable cloud architectures, developed real-time data processing pipelines, and designed backend solutions using different technologies. I am passionate about leveraging data to drive innovation and deliver impactful business insights. Fluent in English and Italian, I thrive in dynamic environments where flexibility and technical excellence are key.
Designing a solution architecture for a document system using MongoDB as the core database technology.
Leading the assessment and design of a new modern data platform on cloud between different alternatives. Experienced in evaluating current data infrastructure, defining architectural strategies, and developing scalable solutions to enhance data management, analytics, and business intelligence capabilities.
Responsible for designing and guiding the implementation of a modern data platform on cloud Azure with Databricks. Experienced in defining data architecture strategies, optimizing data workflows and enabling advanced analytics capabilities to support business objectives and digital transformation initiatives.
Designed and developed backend solution for the GeoIntelligence project using Spring Boot and Apache HBase, with deployment on OpenShift. Responsible for creating scalable and efficient backend architectures, integrating big data technologies, and ensuring reliable operations in a on-premise environment.
Supporting the client in processing data before the loading in the new data platform
During the assessment on RMLT I studied how to migrate the legacy infrastructure based on Oracle and stored procedures for processing to a modern architecture on GCP with BigQuery for the storage and with Apache Spark for processing engine. The main goal is to design a scalable cloud-based solution.
Led the strategic migration of on-premise data lakes from Hadoop/Teradata environments to Google Cloud Platform (GCP), ensuring seamless data transfer and system integration
The infrastructure has different applications, both batch and streaming, aimed at processing data from almost 4 million telematics boxes. Different events are processed in real-time through streaming applications to identify possible incidents. I perform analyses, developments, and tests on CDP using various technologies, mainly Spark and Kafka.
Support for ETL pipeline on GCP cloud.
Developing and testing R scripts on Azure. The main goal was to prepare data for machine learning algorithms.
Proof of Concept for calculating KPIs with Spark on AWS.
Full-stack developer at Technology Reply.
Teaching assistant for the course of Protocols and Architectures for Space Networks M.
Personal skills:
Problem solving
Teamwork
Flexibility
Programming languages:
Java
Scala
Python
Go
C/C
C#
Prolog
HTML
CSS
JavaScript
OS:
Microsoft Windows
Linux (Ubuntu, Fedora, Debian)
IDE:
Eclipse
Visual Studio
Anaconda
IntelliJ
PyCharm
Framework:
Play Framework
Spring Boot
Apache JMeter
Karate Test
Vegeta Test
Angular
AI Tool:
OpenAI (GPT)
Anthropic (Claude)
Google (Gemini)
Codex
Copilot
Big Data:
Hadoop HDFS
Apache Spark
Apache Hive
Apache Impala
Hue
Apache Kafka
AKHQ
Apache NiFi
KSQL
Apache HBase
Apache Flume
Apache Sqoop
Dbt
Apache Airflow
Monitoring:
Splunk
Dynatrace
Zabbix
Platform and Cloud Provider:
Azure
AWS
GCP
Cloudera
OpenShift
Snowflake
Databricks
PowerBI
Fabric
Database (Sql and NoSql):
DB2
Oracle
PostgreSQL
SQL Server
MongoDB
BigQuery
Version Control and CI/CD:
Git
Jenkins
Octopus Deploy
Azure DevOps
SonarQube