E-Commerce Market Intelligence Scraper

Architected robust scrapers using Python and Crawlee, utilizing browser emulation to navigate dynamic e-commerce platforms.

This project involved building a full-scale web intelligence platform capable of extracting structured market data from highly dynamic e-commerce websites. The scrapers use browser fingerprint emulation to avoid bot detection, and the data is processed through a pipeline that normalizes and stores it for downstream analytics. The system is designed for reliability, with automatic retries, error reporting, and Prefect-based orchestration to handle large-scale scheduled runs.