
Developed and enhanced candidate and election management workflows across both frontend and backend in the sigevaFront and sigevaBack repositories. Delivered a new navigation bar UI, an end-to-end candidate management system with CRUD operations, and improved DataTables for richer data handling. Implemented Cloudinary integration for photo uploads and expanded backend routing for more flexible data retrieval. Focused on maintainable architecture and data integrity, leveraging React, Node.js, and TypeScript to streamline onboarding and reporting. Addressed critical bugs in candidate flows and resolved merge conflicts, resulting in faster onboarding, improved data quality, and a more scalable, maintainable system for ongoing development.
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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