
Santos developed and enhanced a candidate management and election workflow system across both frontend and backend in the IngAlim2023/sigevaFront and sigevaBack repositories. He implemented a new navigation bar UI, an end-to-end candidate management interface with modal-based CRUD operations, and improved DataTables for richer data handling. On the backend, he expanded the candidate data model, integrated Cloudinary for photo uploads, and refined API routing using AdonisJS and Node.js. By focusing on data integrity, maintainable architecture, and robust state management with React and TypeScript, Santos enabled faster onboarding, improved reporting, and more scalable, maintainable systems for candidate and election management.

September 2025 (2025-09) – Delivered substantial cross-functional improvements to candidate management and election workflows in both frontend and backend, focusing on business value, data integrity, and maintainable architecture. Key features delivered include a new Navigation Bar UI, an end-to-end Candidate Management System on the frontend with apprentice lists and lesson selection, improved DataTables for elections and selections, and a robust Backend Candidate Management data model with Cloudinary-based photo uploads and expanded CRUD endpoints. Election management enhancements enable listing by training center and time-based filtering, improving reporting and operational decisions. Completed critical bug fixes in the add-candidates flow and resolved merge conflicts to stabilize the codebase. Overall, these changes enabled faster candidate onboarding, richer candidate/election data, and more scalable, maintainable systems. Technologies demonstrated include React with useContext/authContext, Cloudinary integration, Supabase configuration, advanced UI/UX with modals and data tables, and improved routing and preloading.
September 2025 (2025-09) – Delivered substantial cross-functional improvements to candidate management and election workflows in both frontend and backend, focusing on business value, data integrity, and maintainable architecture. Key features delivered include a new Navigation Bar UI, an end-to-end Candidate Management System on the frontend with apprentice lists and lesson selection, improved DataTables for elections and selections, and a robust Backend Candidate Management data model with Cloudinary-based photo uploads and expanded CRUD endpoints. Election management enhancements enable listing by training center and time-based filtering, improving reporting and operational decisions. Completed critical bug fixes in the add-candidates flow and resolved merge conflicts to stabilize the codebase. Overall, these changes enabled faster candidate onboarding, richer candidate/election data, and more scalable, maintainable systems. Technologies demonstrated include React with useContext/authContext, Cloudinary integration, Supabase configuration, advanced UI/UX with modals and data tables, and improved routing and preloading.
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