Roberto Cerrone

design of architecture and support delivery of metadata-driven applications both on-cloud and on-prem. • build an on-cloud data catalog to ingest and process metadata from azure services and app • extract, collect and build lineage of data assets using azure native technology • develop metadata-driven pipeline to migrate ETL procedure and on-prem data to azure

design architecture for ingestion of high volume of data for developing AI models for Autonomous Drive L3 and work for data governance policies enforcement • manage applications running data platform using openshift and mapr clusters • follow delivery of applications on the data platform • deal with stakeholders from business and engineering for data governance compliancies

deliver E2E architecture to ingest reviews from GUCCI systems in form of files, which land on data lake and trigger NLP model. Processed data are saved on sql db and displayed on Tableau dashboards. • provision and deploy architecture using ansible and serverless – infrastructure as a code framework • code NLP model with python using nltk and spacy • create Tableau dashboards to visualize sentiment analysis and topic clustering of the reviews

deliver ETL microservice architecture for a real-time IoT network. • write C# application which ingest, transform and dispatch IoT logs on kafka topics and queues • dockerize it and spin it on a k8s cluster on cloud • the processed logs are written by other C# services which inject them into data warehouse • make DWH data available for analytics and dashboards using Spark and Grafana

deliver AI model which forecasts physical properties of industrial product in real-time and in-line. • code the application in Python using scikit-learn for algorithms (PCA) and signal processing • the model is supervised trained and tested with k-fold, then it is saved on file and used by system's application written in C#