NexGenData LinkedIn Jobs Scraper icon

NexGenData LinkedIn Jobs Scraper

Scrape public LinkedIn job postings for keyword + location — recruiter and sales intel

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Summary

Searches LinkedIn job postings through an Apify actor using required keywords and optional location and job type filters. It returns each result as a separate n8n item; full descriptions are fetched by default.

Inputs

  • Keywords (required) — Job search terms, such as “python developer” or “data scientist.” The value is trimmed before it is sent.
  • Location — Optional location filter, such as “New York,” “Remote,” or “United States.” Defaults to empty for all locations; the value is trimmed.
  • Max Jobs — Maximum number of listings to scrape. Defaults to 50; set to 0 for all available listings.
  • Job Type — Filter by Contract, Full-Time, Internship, or Part-Time. Defaults to Any.
  • Fetch Full Descriptions — Whether to fetch a full description for each listing. Defaults to true; fetching descriptions is slower.
  • Actor Memory (MB) — Memory allocated to the Apify actor run. Defaults to 1024 MB.
  • Run Timeout (Seconds) — Maximum time for the synchronous Apify run. Defaults to 240 seconds; Apify caps synchronous runs at 300 seconds.

Output shape

A list of items, one per returned job listing, with each listing as the item's JSON object.

If the actor returns an object instead of an array, it is wrapped as one item; an empty or non-object response produces no items. With Continue On Fail enabled, an error produces an item containing an error field.

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