As a DevOps Engineer at Holonic, I work in a cross-functional team allocated to an American client that operates in the Remote Healthcare industry. All communication with the client happens in english.My tasks consist of maintaining CI/CD pipelines in Circle CI and Github Actions, supporting staging, tests, and production environments which infrastructure is defined as code using AWS CloudFormation, managing resources access with IAM policies, coordinating releases with the engineering, QA, and product team, actively participating in architecture decisions and supporting engineers by helping them in investigations related to infrastructure and providing environments/resources for tests.

As a software engineer at Zak, I maintained a restaurant back office product. The product managed invoices, cash flows, and inventories, and provided analytic reports. It was marketed with other software for restaurants such as Point of Sales, Operations Dashboards, and Direct to Customer solutions.My tasks consisted of implementing Typescript APIs consumed by other services and a frontend. The application infrastructure was hybrid since it had local servers in the restaurant as well as servers on the cloud. Every feature had to be designed with this architecture in mind, which greatly increased the complexity of calculations and data querying.

As a software engineer at Konduto, I worked in the development and maintenance of an e-commerce fraud prevention platform. The platform used Machine Learning algorithms to detect fraudulent purchases in multiple e-commerce segments.The platform itself consisted of multiple microservices written in Java and Python which communicated using RESTful APIs and message queues. The diverse nature of the data used in the application required multiple data storage solutions, such as relational databases, key-value databases and BLOBs.Besides handling backend demands, I also executed tasks related to the services infrastructure. It usually consisted of maintaining AWS Cloudformation templates, Gitab CI pipelines and automated configurations using Chef.At last, I had the opportunity of being responsible for implementing an internal audit log tool, which gathered events from multiple services, performed normalization and then stored it in a data infrastructure ready for handling big data volumes.

As Software Engineer at Angular, I worked in a cross-functional team that was responsible for understanding customers' business problems, proposing solutions, and implementing them, either in existing systems or creating new ones from scratch.During development, I was the only person focused on the backend and infrastructure. The backend for our solutions consisted of APIs developed in Java and Node.js, using both relational and non-relational databases, such as DynamoDB.Infrastructure was based on AWS Services such as Elastic Beanstalk, Lambda Functions, and RDS. CI/CD pipelines were automated using BitBucket pipelines, and infrastructure was defined as code using CloudFormation.

As a web development intern, I worked on a cross-functional team that was responsible for understanding our customer's business problems, proposing solutions, and implementing them on top of existing systems.During the development of new features, I was the only backend developer, responsible for implementing APIs and managing databases. All infrastructure was hosted on AWS using services like Elastic Beanstalk and RDS.I also created a QA server using idle computers in our office. This server was a replica of our production infra using docker containers, orchestrated with docker-compose, that were manually updated whenever new features were implemented and had to be tested in remote environments.

As a web development intern at Monitora, I worked on the development of an internal tool for a customer that operates in the private jet transport industry. Since it was a customer from outside Brazil, all communication happened in English. The internal tool consisted of a microservice with a backend in Java and a frontend in React.js. The backend exposed data to the frontend using an API, but it also used event queues for processing events from other services. Primary data was stored in a MySQL database, and secondary data was cached in a key-value database.My team followed high-quality standards during software development, so I also did a lot of code reviews, manual tests, and documentation.