Fábio Mendes is Head of Data at Balancer Labs with six years of hands-on experience building data and full-stack solutions for Web3 protocols. He progressed from Data Scientist to Data Engineer and now leads data strategy and execution, combining on-chain SQL analytics with frontend integrations for the Balancer protocol. His open-source contributions include frontend work on balancer/frontend-v2 and SQL views for Dune’s spellbook, reflecting a rare blend of SDK-driven UI scripting and rigorous database design for on-chain datasets. As co-founder of bleu, he pairs product-building instincts with technical leadership, and earlier roles show an ability to deliver industrial-grade dashboards and embedded Industry 4.0 prototypes. Based in Santa Catarina, Brazil, he holds a degree in Control and Automation Engineering and often bridges control-systems rigor with modern data engineering practices. Notably, he focuses on reliable data pipelines that surface protocol governance signals—like voting gauge data—directly into developer and analytics workflows.
6 years of coding experience
4 years of employment as a software developer
Bachelor's degree Control and Automation Engineering, Bachelor's degree Control and Automation Engineering at Universidade Federal de Santa Catarina
Electrotechnical Technician, Electrotechnical Technician at IFSC - Instituto Federal de Santa Catarina
Contributions:23 reviews, 27 commits, 32 PRs in 1 year 11 months
Contributions summary:Fábio primarily contributes by adding and modifying SQL views within the `duneanalytics/spellbook` repository. Their commits involve adding new ERC20 tokens to a database table and creating new views for analyzing data related to Balancer. They are also focused on enhancing the functionality by adding new views and fixing existing indices. The user demonstrates expertise in database design, specifically in the context of on-chain data analysis.
Contributions:5 reviews, 34 commits, 34 PRs in 9 months
Contributions summary:Fábio primarily contributed to the frontend of the Balancer protocol, focusing on implementing and generating scripts related to voting gauges. Their work involved interacting with the Balancer SDK, fetching data from subgraph endpoints, and creating scripts for generating JSON files containing gauge information. Furthermore, the user demonstrated proficiency in integrating with external APIs for token logo retrieval and made several code enhancements related to error handling and address formatting.
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