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redaellimattia/README.md

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๐Ÿ‘‹๐Ÿผ Hi, Iโ€™m @redaellimattia

My name is Mattia Redaelli and I am a Computer Science & Engineering graduate from Polimi, specializing in Big Data and AI technologies. As a Data Engineer at Quantyca, I daily apply my expertise to tackle real-world challenges in the dynamic field of data engineering. Passionate about leveraging technology for innovative solutions, I am dedicated to staying at the forefront of industry trends. Outside of work, I thrive on staying active through outdoor sports. I am excited about the opportunities to further develop and challenge myself both professionally and personally. Here's something about me:

๐Ÿ’ผ Work Experience

Data Engineer @Quantyca

Terraform Apache Kafka Snowflake Java Spring Azure GCP

  • Development of a comprehensive Data Platform on Snowflake, integrating Data Mesh principles to enhance data accessibility and governance.
  • Leveraged Apache Kafka for real-time data streaming, employed Terraform for infrastructure management, and utilized cloud services such as Azure and GCP for scalable, secure solutions; developed microservices with Spring Boot for data processing needs.
  • Contributed to collaboration and project management efforts by working with cross-functional teams, and applying advanced technologies to help achieve organizational goals.

Frontend Engineer @Fundvis

Angular TypeScript TailwindCSS

  • Led the design and maintenance of a scalable and robust front-end architecture for Fundvis, ensuring seamless user experiences and integration with backend systems.
  • Utilized modern front-end technologies including Angular, TypeScript, and Tailwind to build and optimize user interfaces.
  • Developed strong collaboration skills by working closely with cross-functional teams within an Agile methodology, translating client needs into actionable features, and driving project success through effective communication and teamwork.

๐Ÿงช Projects

Python Pandas SciPy
Competition of the course of Recommender Systems at the Polytechnic University of Milan. Competed with other students to create a model for recommending new tv series to users of a given dataset.

Python Keras TensorFlow
The aim of the project is to predict future samples of a multivariate time series. Project developed during the course of Artificial Neural Networks and Deep Learning at the Polytechnic University of Milan.

Python Keras TensorFlow
The task was to develop a model for classifying images and to train it to distinguish between 14 classes of leaves. Project developed during the course of Artificial Neural Networks and Deep Learning at the Polytechnic University of Milan.

Java
Software Engineering Final Project - BSc thesis.
Modeling a board game as software, enabling remotely played games using sockets, and implementing all game rules. Playable both from CLI and GUI. Developed using Java, and JavaFX for the GUI. Implemented using Model View Controller architectural pattern (MVC).

C
Algorithms and data structures project. The project consists in a text editor written in C, with the possibility of performing multiple undo and redo, during insertions, as well as the usual printing and deleting.

๐Ÿ”ง Other Technologies & Tools

Jira Postman MySQL GitHub Actions

๐Ÿ™Œ๐Ÿฝ Connect with me

LinkedIn

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  1. RecSys-Competition-2022-Polimi RecSys-Competition-2022-Polimi Public

    This repository contains the code used during a Recommender Systems competition, which is part of the course of Recommender Systems at the Polytechnic University of Milan.

    HTML

  2. DL-Time-Series-Forecasting DL-Time-Series-Forecasting Public

    The goal of the project is to predict future samples of a multivariate time series.

    Jupyter Notebook 1

  3. DL-Leaves_Images_Classificator DL-Leaves_Images_Classificator Public

    Forked from GabrieleRivi/Leaves_Images_Classificator

    The task was to develop a model for Image Classification and to train it to distinguis between 14 classes of leaves, as in the example below.

    Python

  4. Progetto-SWE-2021 Progetto-SWE-2021 Public

    Implementazione del gioco da tavolo Masters of Renaissance

    HTML 2