LAGIC
Lead Audience Growth Intelligence Computing
L

Linkedin Jobs Scraper — LinkedIn | Lagic

Built For

Extract detailed job postings from LinkedIn searches for market analysis and lead generation.

Curated by Lagic·Verified working

Configure Agent

Go to linkedin jobs search page on incognito window (to access public version), search with required filters and once you are done, copy the full URL from address bar and pass it here. You can pass multiple search URLs

This will require additional scraping requests for each job record and take longer to scrape

Limit number of jobs scraped

Enable this to split your search by cities within a country. This helps bypass LinkedIn's 1000 job limit per search URL by creating separate searches for each city. This will overwrite the location filter in input search URLs.

Select the country whose cities will be used to split the search. Only used when 'Split search by city locations' is enabled. Required to when 'Split search by city locations' is enabled.

Results to deliver

100 credits

This agent actively searches live listings — results may vary. You are only charged for what is delivered, up to this number.

Lagic Proxy

Country auto-rotated. Need a specific region? Contact support.

Pricing

1 credit per result
✓ 30 free credits on signup✓ Refund if 0 results✓ No card required

Sample Data Preview

Job Title and Full Description (HTML and text)Company Name, Website, Employee Count, and DescriptionSalary Range and Compensation Details (when available)Location, Workplace Type (e.g., Remote, Hybrid), and Remote Work EligibilityEmployment Type (e.g., Full-time, Contract) and Seniority LevelDate of Posting and Expiration
Sample Text...Sample Text...Value...100962026-04-052026-04-05
Sample Text...Sample Text...Value...100922026-04-052026-04-05
..................
Exports as:CSVXLSXJSON

Overview

Scrape LinkedIn job postings using search URLs to gather data like company details, salary ranges, and job descriptions. Ideal for recruitment agencies, market researchers, and B2B sales teams.

This tool extracts comprehensive data from LinkedIn job postings based on your search queries. It's designed for recruiters, sales teams, and market analysts who need structured data on hiring trends, open positions, and company growth signals. By providing one or more LinkedIn job search URLs, you can collect a dataset that includes not just the job title and description, but also rich company information like employee count, website, and industry. The tool can also capture salary insights, required skills, and details about the person who posted the job, when available. A key feature is the ability to bypass LinkedIn's 1000-job limit per search. By enabling the 'Split search by city locations' option, the tool programmatically runs your search across major cities within a selected country, aggregating the results into a single, more complete dataset. Use this data to build a pipeline of open roles, identify companies with specific technology needs (by searching for keywords in descriptions), monitor competitor hiring activity, or analyze the job market in a specific region or industry.

Key Capabilities

  • Job Title and Full Description (HTML and text)
  • Company Name, Website, Employee Count, and Description
  • Salary Range and Compensation Details (when available)
  • Location, Workplace Type (e.g., Remote, Hybrid), and Remote Work Eligibility
  • Employment Type (e.g., Full-time, Contract) and Seniority Level
  • Date of Posting and Expiration
  • Job Poster's Name and LinkedIn Profile URL (when available)
  • Direct Application Link
  • List of Stated Job Benefits
  • Industry and Job Function Classifications
  • a recruitment agency — build a pipeline of all open software developer roles in Germany to source candidates for. — get ahead of competitors and find opportunities not listed on standard job boards.
  • a B2B SaaS sales manager — find all companies currently hiring 'Salesforce Administrators' or 'Marketing Automation Specialists'. — identify warm leads who have a clear need and budget for my company's software integration.
  • a market research analyst — track the number and type of AI-related job postings in the US financial sector over time. — publish a report on technology adoption trends and skill demand in the industry.
  • a commercial real estate broker — identify companies that are rapidly expanding their sales teams in Austin, Texas. — proactively reach out to them with proposals for new office space.
  • a university career services advisor — extract all entry-level marketing jobs posted by Fortune 500 companies. — create a curated list of relevant opportunities for recent graduates.
  • a freelance consultant — monitor for short-term or contract-based 'Project Manager' roles in the renewable energy sector. — find and apply for new consulting gigs as soon as they are posted.

Field Dictionary

How To Run This Extractor

1

Open a new incognito or private browser window.

2

Go to the LinkedIn Jobs search page and enter your desired keywords and filters.

3

Once you see the results, copy the full URL from your browser's address bar.

4

Paste one or more search URLs into the 'Linkedin jobs search URLs' field.

5

To get more than 1000 results, enable 'Split search by city locations' and select a country.

6

Run the tool and download your job data in a spreadsheet or JSON format.

Frequently Asked Questions

Why do I need to use an incognito window for the search URL?
Using an incognito window ensures you get the public, non-personalized version of LinkedIn's search results, which is what the tool needs to access the data reliably.
What does the 'Split search by city locations' option do?
Can I scrape jobs that require a LinkedIn Premium account to view?
Will I get the email address of the hiring manager?
What format does the data come in?
Is this difficult to use if I'm not a developer?
Is it legal to scrape LinkedIn job postings?
How many jobs can I scrape at once?
Can I use this for client work at my agency?
How fresh is the data?
Can I schedule this tool to run automatically?