Turn a public job-posting URL into structured job data.
Extract title, company, location, salary when present, employment type, publication/valid-through dates, source URL, and Schema.org JobPosting metadata for automation, analytics, or export.
Designed for known public job URLs.
This is a page-to-structured-data workflow. It is useful when you already have one or more public job-posting URLs and need normalized fields downstream.
Structured export
Normalize common job fields from public posting pages.
Salary & dates
Capture compensation and date fields when the source exposes them.
Automation
Call through the Apify REST API and consume Dataset output.
Schema.org aware
Use JobPosting structured metadata where available on the source page.
Minimal API call.
curl -X POST \
"https://api.apify.com/v2/acts/signal_lab~job-vacancy-scraper/runs" \
-H "Authorization: Bearer $APIFY_TOKEN" \
-H "Content-Type: application/json" \
-d '{
"urls": ["https://example.com/public-job-posting"],
"maxJobs": 5,
"maxItems": 5
}'Use public pages you are authorized to process. The Actor does not claim to search every job board or bypass login walls.
Common use cases.
- Feed structured job rows into internal recruiting or market-intelligence workflows.
- Export known public postings into CSV/JSON pipelines.
- Normalize salary, location, employment type, and date fields across sources where those fields exist.
- Extract Schema.org JobPosting metadata for downstream analysis.
Pricing and limitations.
Pricing can change; use the live Apify Pricing tab as the source of truth before running. Output quality depends on what the public source page exposes. Missing source fields cannot be guaranteed.
Run the live Job Vacancy Scraper.
Inspect current input and pricing on Apify, then start with a small bounded run.