Cj V.

I build web scrapers and data pipelines that stay alive in production — including on sites with aggressive bot detection. After 5+ years, the #1 reason scrapers fail is the same: they get detected within days. I build collection that behaves like real traffic, respects rate limits, and delivers clean structured data on schedule, so you stop paying for re-fixes. What I deliver • Multi-site, multi-country scraping systems with reusable architecture • Resilience against modern anti-bot systems (Cloudflare, DataDome, PerimeterX) through proper browser automation, proxy management, and pacing • Scheduled pipelines into BigQuery, PostgreSQL, Google Sheets, or your database • Stabilization of broken or inherited scrapers, with monitoring and change detection Recent work • Multi-country e-commerce product and price monitoring across Europe and Asia — Sheets output plus BigQuery history • Multi-market product data platform for an enterprise client (Kubernetes-orchestrated, BigQuery warehouse) • ~1M-row public records pipeline rebuilt from fragile to production-grade Stack: Python, Playwright, Scrapy, curl_cffi, Docker, Kubernetes, GCP, BigQuery, PostgreSQL Best fit: scrapers that keep breaking, high-protection or multi-site targets, pipelines that must run unattended for months. Send the site or pipeline that's causing trouble and I'll tell you how I'd approach it.