Automation engineer who builds scrapers that actually scale — 2.3M records extracted, 40K+ in under an hour.
At my previous role with ListingsLab (US-based, remote), I owned data pipelines end-to-end:
- Scraped 2.3M property records from Trulia/Zillow despite aggressive bot detection
- Built ETL pipelines: FastAPI > SQS > Lambda > Batch > PostgreSQL
- Pulled and normalized data from public sources (US Census, SpotCrime, GreatSchools)
- Implemented IP rotation, 2Captcha integration, and resilient retry logic
- Containerized everything with Docker, deployed on AWS
Tech stack: Python, Playwright, Selenium, BeautifulSoup, httpx/curl_cffi, FastAPI, Docker, AWS (Lambda, SQS, Batch), Supabase/PostgreSQL
I make data collection fast, reliable, and respectful of rate limits.
API-first approach — I reverse-engineer endpoints before falling back to browser automation.
Open to: Web scraping, data pipelines, ETL, backend automation, API integration.
