Summary
Matheus Gritz is a Data AI Engineer based in São Paulo with a decade of experience building scalable data and payment systems that bridge software engineering and applied ML. At Dock he modernized data infrastructure, built GenAI assistants that cut support time by 40% with high accuracy, and implemented Databricks ETL pipelines that automated documentation and saved 20 hours monthly. He has driven major backend migrations (Java → event-driven + Go) that reduced cloud costs by 35% and cut latencies by up to 60% while raising reliability above 99.9%. Earlier work at LNCC combined scientific HPC profiling with ML to predict energy and performance, reflecting a strong foundation in computational measurement and efficiency. Matheus pairs hands-on implementation (Python, FastAPI, Databricks, PostgreSQL, Kafka, Go) with pragmatic cost and observability optimizations, including token-aware LLM cost reductions. He’s pragmatic, metrics-driven, and comfortable turning research-grade prototypes into production-grade, low-latency systems.
10 years of coding experience
6 years of employment as a software developer
Superior em Tecnologia da Informação e Comunicação, Computer Science, Superior em Tecnologia da Informação e Comunicação, Computer Science at Faeterj Petrópolis - Faculdade de Educação Tecnológica do Estado do Rio de Janeiro- Campi Petrópolis
Técnico em Informática e Comunicação, Tecnologia da Informação, Técnico em Informática e Comunicação, Tecnologia da Informação at Instituto Federal de Educação, Ciência e Tecnologia do Sul de Minas Gerais
English, Portuguese