Matheus Sampaio is a data engineer with nine years in tech and over four years focused on building scalable ELT pipelines, data warehouses, and real-time processing platforms across AWS, GCP and Databricks. He has driven high-impact projects—from processing terabytes of 5G test data with Kafka and Flink to powering recommendation engines for millions of users using Airflow and Spark—delivering measurable gains in model accuracy and user engagement. Comfortable in Python, SQL, Scala and infrastructure-as-code with Terraform, he combines strong dimensional modeling and performance tuning skills with hands-on ML/NLP experience that cut anomaly detection effort by 40%. Currently at EPAM, he’s helping ship a unified conversational AI platform on GCP that serves real-time model responses for food ordering, showing an uncommon blend of streaming engineering and applied AI. Based in Ceará, Brazil, he pairs academic specialization in deep learning and LLMs with practical production experience, making him effective at turning research ideas into reliable data products.
9 years of coding experience
6 years of employment as a software developer
Barchelor Computer Science, Barchelor Computer Science at Federal University of Ceara
Computer Science Specialization Deep Learning and LLM, Computer Science Specialization Deep Learning and LLM at Universidade Estadual de Campinas
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