Guilherme Penna
Lavras
Summary
Software Engineer with over 4 years of experience in building distributed, scalable, and high-performance systems. I am proficient in the entire Node.js ecosystem, with a specialization in TypeScript, NestJS, and Express. I have extensive experience in data modeling and optimization, utilizing MongoDB, implementing messaging architectures with RabbitMQ, and leveraging Redis for caching and state management. With a solid foundation in Docker, Git, and agile methodologies like Scrum, I am focused on delivering robust, high-value solutions. Throughout my career, I have had the opportunity to develop high-impact projects, including optimizing a critical MongoDB query that reduced latency from 40 seconds to 0.2 seconds, unblocking the business team's productivity. I have developed microservice ecosystems from scratch, such as a referral system and a live-streaming platform with real-time communication via Sockets, and have also automated manual financial processes through asynchronous and resilient workflows. These initiatives were fundamental in driving new customer acquisition and improving the company's operational efficiency. My professional goal is to continue solving complex engineering challenges by applying my knowledge in software architecture to build products that not only perform excellently but also generate a significant and positive impact on the business and its users. Experienced with creating robust software applications tailored to client needs. Utilizes advanced coding techniques to ensure seamless performance and scalability. Strong understanding of software development lifecycle and agile methodologies.
Overview
5
5
years of professional experience
Work History
Software Engineer
Anota AI
07.2022 - Current
- - I developed a referral microservice in NestJS and TypeScript, orchestrating the integration with an external platform to automate the rewards system. To ensure system resilience, I utilized RabbitMQ to manage a message queue with reprocessing capabilities, thereby preventing data loss in the event of failures. This project was fundamental in driving new customer acquisition by transforming existing users into an organic growth channel for the company.
- - I automated the customer reactivation flow by developing a microservice in NestJS that consumes webhooks from a payment platform. To ensure the system's robustness, I used RabbitMQ to create a message reprocessing workflow and Redis for concurrency control, preventing duplicates and subscription errors. This automation eliminated a manual process for the finance team, improved the customer experience, and guaranteed the integrity of reactivations.
- - I optimized a critical search route in Node.js and MongoDB that had response times of up to 40 seconds, directly impacting the Business team's productivity. By refactoring a Mongoose aggregate query and implementing a strategic indexing plan—creating compound and individual indexes for filter and $lookup fields—I eliminated the need for full collection scans. This resulted in a more than 99% improvement in response time (from 40 seconds to 0.2 seconds), which unblocked the team by enabling real-time customer queries and significantly accelerating support services.
Software Engineer
Zeester
08.2020 - 06.2022
- - I re-architected the data model of a content system in MongoDB, which previously relied on three interconnected collections, resulting in multiple complex queries. I implemented a denormalization strategy, consolidating information into a single document using indexed references. This change drastically optimized query performance, enabling users to retrieve data far more efficiently. Concurrently, it streamlined the development workflow, enabling the engineering team to maintain and extend the feature more efficiently with cleaner, more direct code.
- - I built a complete microservice in Node.js to manage live streaming, leveraging Socket.io for real-time communication, Redis for dynamic data storage, and MongoDB for persistence. This solution empowered content creators to schedule and host live events independently, while enabling users to watch and interact in real-time. After each event, the system persisted the full history and engagement metrics, establishing a new and valuable form of interaction on the platform.
Education
Bachelor of Science - Information Systems Management
Universidade Federal De Lavras
Lavras, Minas Gerais, Brazil01.2022
Skills
- Nodejs,
- NestJS,
- Express,
- TypeScript,
- JavaScript
- MongoDB, Redis
- RabbitMQ
- Docker
- Git,
- Scrum
Timeline
Software Engineer
Anota AI
07.2022 - Current
Software Engineer
Zeester
08.2020 - 06.2022
Bachelor of Science - Information Systems Management
Universidade Federal De Lavras