Building a job board is a classic developer project, but the real challenge isn't building the frontend—it's maintaining the data. Job postings expire quickly, formatting is always inconsistent, and manual data entry is a nightmare. To solve this, I designed a fully automated architecture that scrapes, structures, and publishes job postings without human intervention. Here is how I built the pipeline using Next.js , Prisma , and n8n . The Architecture at a Glance Instead of relying on a traditional CMS, I wanted a highly scalable, developer-friendly stack: n8n: The brain of the operation. It handles the cron jobs, web scraping, and API orchestrations. Prisma: The ORM that safely handles our database schema and migrations. Next.js: The frontend framework delivering blazing-fast SSR/SSG pages, which is crucial for SEO. Step 1: Automating Data Collection with n8n Writing custom Python scripts for scraping is fine, but managing their execution and failures is tedious. I used n8n to create visual workflows.…