Hugo Cavalari
About Hugo Cavalari
Hugo Cavalari is a Lead Data Engineer at Thoughtworks in São Paulo, Brazil, with extensive experience in data engineering and architecture. He has worked for various companies, including Itaú Unibanco and Klabin, and holds multiple degrees in Information Technology and Organizational Leadership.
Work at ThoughtWorks
Hugo Cavalari has been serving as the Lead Data Engineer at ThoughtWorks since 2021. In this role, he is responsible for deploying and sustaining systems that generate significant billing, amounting to 1 billion per month. His work involves influencing clients in making data architecture decisions and building enterprise-level data strategies. He has also played a key role in adapting and connecting the Grupo Globo video streaming platform in Brazil to implement the data mesh.
Previous Experience in Data Engineering
Before joining ThoughtWorks, Hugo Cavalari held several positions in data engineering and related fields. He worked as an AWS Data Engineer II at Itaú Unibanco from 2017 to 2020, where he gained experience in cloud-based data solutions. He also served as a Big Data Specialist at Leega for five months in 2020 and as an Analista de Suporte at Klabin from 2012 to 2013. His earlier roles included positions at Hypermarcas and Safra, where he focused on systems analysis.
Education and Expertise
Hugo Cavalari has a strong educational background in information technology and management. He studied at Universidade de São Paulo, earning an MBA in Gestão de Pessoas with an emphasis on Organizational Leadership from 2021 to 2023. He also completed a specialization in Big Data at the same university from 2019 to 2020. Additionally, he has qualifications in ABAP Development and holds a degree in Computer Science from Anhanguera Educacional.
Technical Skills and Projects
Hugo Cavalari possesses extensive technical skills in data engineering, particularly in integrating and acquiring external databases for credit risk modeling processes. He has participated in large-scale projects for big data systems in Hybrid Clouds, specifically utilizing AWS and GCP. His expertise includes setting up fully defined end-to-end CD4ML processes, ensuring model training, reproducibility, deployment, and monitoring.