Web Scraper with 3+ years of production experience designing and maintaining robust scraping scripts and pipelines that extracted 50,000+ records daily from both static and dynamic websites using Python, Selenium, and Scrapy. Skilled in cleaning, validating, and structuring large volumes of data for downstream use, and experienced implementing anti-scraping bypass solutions that increased data collection success rates by 40%.
Comfortable working with REST APIs, JSON/XML parsing, and both relational and NoSQL databases.
Communicates clearly with clients to define data requirements, documents processes for reusability, and
troubleshoots issues autonomously in remote, async-first settings
• Tasked with reliably extracting product and pricing data from both static and dynamic pages across 7 major e-commerce platforms, designed and maintained scraping scripts in Python, Selenium, and Scrapy, sustaining 50,000+ records/day
• To ensure data quality before delivery, built cleaning, validation, and deduplication steps into every pipeline, catching issues before they reached downstream systems
• When target platforms implemented new anti-scraping mechanisms, implemented rotating proxies and browser fingerprint spoofing to maintain scraping effectiveness, increasing data collection success rates by 40%
• Monitored scraping pipelines daily for data quality issues and troubleshot failures autonomously, resolving root causes with minimal downtime
• Collaborated with the business team to define data requirements, and documented scraping processes and code for long-term scalability and reusability
