How MongoDB Powers My Intelligent Job Matcher Application Introduction When I built Intelligent Job Matcher, I wanted one database that could handle flexible documents, quick iteration, and multiple feature modules without rigid schema migration every time I changed a field. MongoDB became the core data layer of the project. In this blog, I explain: Why I chose MongoDB At which level MongoDB is used Real project code snippets End-to-end data flow from UI to API to MongoDB Lessons learned and next improvements Project Demo Watch the complete project demo below: Why I Chose MongoDB for This Project I selected MongoDB because my application stores multiple types of data that evolve over time: User profiles and authentication records Job documents with titles and descriptions Resume submissions Explainability reports with dynamic fields Analytics history records Job role taxonomy entries A document database fits this use case very well because: Structure can vary between collections Development is fast for…