Jonatas S. O. Vieira

Architected and implemented a scalable data processing platform using Java, Python, Apache Kafka, and Kafka Streams to handle high-volume data preparation.

Integrated Open Telemetry and Spring Sleuth for comprehensive distributed tracing and observability across microservices, improving system diagnostics and performance monitoring.

Utilized Docker and Kubernetes for efficient container orchestration and deployment, ensuring high availability and seamless scaling of critical data infrastructure.

Implemented robust monitoring and logging solutions with Grafana and the ELK stack (Elasticsearch, Logstash, Kibana) to provide real-time insights into platform health and operational metrics.

Designed and implemented a comprehensive API, developed with Java and Python, to manage end-to-end freight hiring processes and generate shipping labels for multiple carrier partners.

Leveraged AWS EKS, SNS, and SQS to build a highly available and scalable microservices architecture, ensuring robust communication and efficient message queuing.

Utilized Spring Boot and Spring Data with PostgreSQL for efficient data management and persistence, optimizing API performance and data integrity.

Integrated JasperReports for dynamic label generation and ZPL for printer compatibility, enhancing operational efficiency and accuracy in logistics processes.

Managed containerized deployments with Docker and Kubernetes, and optimized data caching with Redis for improved API response times and user experience.

Contributed to a project that enabled Brazilian banks to achieve R$2 billion in savings by successfully re-architecting mainframe-based services into a modern microservices architecture.

Developed high-performance microservices using Java and Python with Spring Boot, enhancing system agility, scalability, and maintainability.

Migrated critical banking functionalities from legacy mainframes to a cloud-native environment, leveraging Docker, Kubernetes, and AWS Fargate for robust deployment.

Implemented resilient data persistence layers with SQL Server and Spring Data, ensuring high data integrity and efficient transaction processing for financial applications.

Integrated RabbitMQ for asynchronous messaging, improving inter-service communication and overall system resilience within the banking infrastructure.

Designed and implemented a data tracking system for Brazilian telco companies, monitoring the entire range of mobile IP addresses assigned to customers.

Processed and managed a massive volume of daily logs and IP change data, enabling comprehensive historical analysis and real-time querying capabilities.

Utilized Java, Groovy, and Python with Spring Boot to build scalable backend services for data ingestion and processing.

Implemented data pipeline automation with Apache NiFi and integrated monitoring tools like Mmonit, NetSNMP, Grafana, and Riemann.io for comprehensive system health oversight.

Deployed solutions using Docker and Kubernetes, ensuring efficient resource management and high availability for critical data services.

Managed authentication and authorization with FreeRadius and Keycloak, and facilitated high-speed data search and analysis with Elasticsearch.

Engineered and enhanced internal enterprise systems using Java, Spring Boot, and Python to optimize operational workflows across various departments.

Developed user interfaces with ReactJS and JSF, significantly improving the usability and efficiency of internal tools for diverse business functions.

Implemented advanced search functionalities and data indexing with SOLR, enabling quick and accurate access to critical tax-related information.

Contributed to the full software development lifecycle, from requirements gathering to deployment, ensuring the delivery of robust and reliable internal applications.