Job boards are among the hardest sites to scrape. Indeed, Monster, CareerBuilder and similar platforms have invested heavily in anti-automation for over a decade — rate limits, fingerprinting, CAPTCHAs, and legal pressure.
Our client, a popular US job portal, needed daily extraction from 20 sources: job titles, locations, wages, company profiles, descriptions, and candidate resume metadata.
Phase 1 — Discovery: we mapped each site's structure, API endpoints (where available), and anti-bot stack. Phase 2 — Extraction: custom spiders per site with shared normalization pipeline. Phase 3 — Delivery: CSV via FTP for validation, then direct PostgreSQL insertion.
Results: 1.5 million listings on the initial backfill. 180,000 clean structured records per day thereafter. Zero client-side infrastructure — we handle proxies, retries, and schema changes.
The client estimated this was 20× cheaper than building an in-house team. Job sites change layouts frequently; outsourcing maintenance was the decisive factor.
Similar project? Our job aggregation packages start with a requirements call. We typically quote within 6 hours and deploy within 48 hours.
