• Desenvolvimento de integrações entre sistemas terceiros e sistema de gerenciamento de combustíveis para frotas de caminhões utilizando Java;• Desenvolvimento de novas funcionalidades e correções de bugs; • Manipulação das bases de dados relacionais PostgreSQL; • Vivência em ambiente de desenvolvimento dockerizado.

• Led front-end and back-end development with React, JavaScript, Java, and Spring Boot, delivering complete and efficient solutions, following clean code and SOLID principles.• Developed a peer review platform used by analysts to submit and evaluate SQL scripts and data models, leading to improved script quality and data model consistency.• Implemented unit tests with JUnit following Test-Driven Development (TDD), ensuring high code quality and minimizing production failures.• Participated in planning and alignment meetings with the client, following Agile practices, to ensure project goals were understood and met, fostering transparency and collaboration throughout the development lifecycle.• Version management with CI/CD and Gitflow, optimizing the development cycle with continuous integration, automated testing, and continuous delivery.

• Implementation of RESTful APIs with Java, Spring Boot, Node.js, and NestJS, enhancing interaction between users and systems for a flexible benefits company.• Developed unit tests using JUnit to ensure the correct functioning of business logic;• Front-end development with Angular and React in various projects;• Creation, maintenance, and management of relational databases (MySQL and PostgreSQL), ensuring data integrity and performance.• Driving the development cycle using agile methodologies such as Scrum and Kanban in Jira, promoting an organized and efficient work environment.

• Led full-stack development of web applications using Vue.js, Express, Node.js, and Docker, optimizing researchers' time in Natural Language Processing (NLP) - an area of Artificial Intelligence - when handling large amounts of linguistic data.• Developed Python/Bash scripts for processing and scraping linguistic data, enhancing data collection and analysis capabilities.• Implementation and deployment of applications into production on Linux virtual machines for use by researchers, resulting in the adoption of tools by various experts and subsequent publication of papers in renowned NLP conferences.• Use of Python, Git, MongoDB, JavaScript, Vue.js, Node.js, Express, and Docker in the development and implementation of solutions.