Josué K.

1. Led the development of a user data microservice to enhance user experience and data integrity by spearheading the design and implementation using Go, Cassandra, and Redis. This focused on robust data management and efficient access, which ultimately improved user data accuracy and system stability, contributing to a more reliable overall experience.

2. Designed a scalable microservices to boost system performance and availability by designing a high-availability architecture that ensured scalability and resilience. This resulted in enhanced system performance and uptime, leading to a more reliable and responsive user experience.

3. Collaborated cross-functionally to convert business requirements into technical specifications by engaging with product managers, designers, and other stakeholders to gather and refine requirements. This effort streamlined the development process, facilitating more efficient project execution and better alignment with business goals.

4. Developed microservices for aggregating sports data through seamless integration by creating solutions with Go, Kafka, and Postgres to efficiently process and aggregate data. This enabled timely and accurate delivery of sports information, significantly enhancing the overall user experience and data quality. 5. Conducted comprehensive code reviews and mentored junior developers to uphold high coding standards and foster professional growth. Provided constructive feedback and guidance on best practices, which led to improved code quality, enhanced team collaboration, and accelerated the development process.

1. Designed and developed a mentoring system to match mentors and mentees according to their skills and preferences by implementing a matching algorithm within the HR application. This system facilitated better alignment between mentors and mentees based on their expertise and interests, leading to a more effective mentoring program and increased user satisfaction.

2. Built an API to enable fast search across squads, chapters, guilds, and teams by developing a robust and efficient search service integrated into the HR application. This API significantly improved search performance, allowing users to quickly and accurately find relevant information across various organizational units.

3. Set up a cache with Redis to improve search performance by implementing caching mechanisms for frequently accessed search queries. This enhancement reduced response times and improved overall application performance, resulting in a more responsive user experience.

4. Developed tasks for extracting, transforming, and loading (ETL) data from internal applications into the HR application by creating processes to seamlessly integrate and synchronize data. This ensured consistent and accurate data availability, enhancing the functionality and reliability of the HR application. 5. Implemented an endpoint to store users' CVs and profile pictures in Google Cloud Storage by creating a service for managing and storing these files. This solution enabled secure and efficient storage, improving the management of user profiles and making data retrieval more streamlined.

1. Enhanced and managed data center applications, ensuring smooth monitoring and operations by utilizing Python Django and Golang. This involved improving application performance and reliability through proactive management and optimization, resulting in more efficient monitoring and smoother operations within the data center environment.

2. Optimized device polling to reduce errors to under 1% for 30,000 devices by redesigning the system with Celery and Redis. This overhaul of the device polling system significantly decreased error rates, ensuring more accurate data collection and reliable device performance.

3. Streamlined billing processes by implementing distributed event processing with Python Django and Golang, reducing processing time from 3 days to 1 day. This improvement in event handling and processing efficiency led to faster and more accurate billing operations.

4. Created a Modbus RTU to TCP converter service and a power usage effectiveness (PUE) calculator API using Python Django and Golang for energy efficiency assessment. These tools facilitated better energy management by providing accurate data conversion and efficiency metrics, enhancing overall energy efficiency in the data center.