Linkedin Jobs Scraper

Scrape job listings from LinkedIn, the world's largest professional network. Extract job titles, companies, salaries, technologies, and more with structured JSON output.

Two Scraping Modes

This actor offers two modes to balance speed vs. data richness:

Basic Mode (fetchFullDetails: false)

• Speed: 200 jobs per minute
• Data: Job title, company, location, posted date, work model (from card)
• Best for: Quick job counts, large-scale listings, fast prototyping

Full Details Mode (fetchFullDetails: true)

• Speed: 25 jobs per minute
• Data: Everything in basic mode + full description (3,000-6,000+ chars), salary, experience level, employment type, applicants count
• Best for: Deep analysis, salary research, skill demand analysis

Recommendation: Start with full details mode for comprehensive data. Use basic mode only when you need very large datasets quickly.

Quick Start

1. Open on Apify Console
2. Enter your search parameters
3. Click Run
4. Download results from the Dataset tab

{
  "keywords": "python developer",
  "location": "Spain",
  "jobsNumber": 50,
  "fetchFullDetails": true
}

Input Parameters

Parameter	Type	Required	Default	Description
keywords	string	Yes	-	Search term
location	string	No	Spain	City or country
workModel	string	No	-	remote, hybrid, or onsite
jobsNumber	integer	No	200	Target count (min: 20)
fetchFullDetails	boolean	No	false	Fetch full job details from each job page

Output

Each scraped job includes:

{
  "id": "3847265819",
  "title": "Senior Python Developer",
  "company": "TechCorp",
  "companyUrl": "https://www.linkedin.com/company/techcorp",
  "location": "Madrid, Spain",
  "description": "We are looking for an experienced Python developer to join our backend team...",
  "url": "https://www.linkedin.com/jobs/view/3847265819",
  "workModel": "hybrid",
  "postedDate": "2026-03-20T12:00:00.000Z",
  "technologies": ["python", "fastapi", "aws", "docker", "postgresql"],
  "salary": "30k - 50k EUR per year",
  "experienceLevel": "Senior",
  "employmentType": "Full-time",
  "applicants": 42
}

Output Fields

Field	Type	Description	Full Details Only
id	string	Unique LinkedIn job ID	No
title	string	Job title	No
company	string	Company name	No
companyUrl	string	Company LinkedIn profile URL	No
location	string	Job location	No
description	string	Full job description (3,000-6,000+ chars with full details)	Yes
url	string	Direct LinkedIn job posting URL	No
workModel	string	remote, hybrid, or onsite	No
postedDate	string	ISO 8601 date when job was posted	No
technologies	string[]	Detected technologies from description (better with full details)	No
salary	string/null	Salary as shown on LinkedIn (e.g., "30k - 50k EUR per year")	Yes
experienceLevel	string/null	Senior, Mid-Senior, Junior, etc.	Yes
employmentType	string/null	Full-time, Part-time, Contract, etc.	Yes
applicants	number/null	Number of applicants	Yes

Features

Feature	Description
Keyword Search	Search any job title, skill, or industry
Location Filter	Target cities and countries worldwide
Work Model	Filter remote, hybrid, or onsite positions
Tech Detection	Auto-extracts 400+ technologies from descriptions
Salary Data	When available on LinkedIn
Experience Level	From job page when displayed
Employment Type	From job page when displayed

Important Notes

• Full Details Only fields: The following fields are only populated when using fetchFullDetails: true: description, salary, experienceLevel, employmentType, applicants. In basic mode, these fields will be empty or null.
• Salary data: LinkedIn does not always display salary publicly. The salary field will be null unless the employer chose to show it.
• Work Model: Extracted from job page when displayed by employer.
• Technologies: Detection is significantly better with full details mode because it analyzes the complete job description.

Use Cases

Salary Analysis

{
  "keywords": "python developer",
  "location": "Spain",
  "jobsNumber": 100,
  "fetchFullDetails": true
}

Extract salary data across roles to build compensation reports.

Skills Demand

{
  "keywords": "data scientist",
  "location": "Remote",
  "jobsNumber": 200,
  "fetchFullDetails": true
}

Collect technologies from hundreds of postings to identify in-demand skills.

Remote Work Trends

{
  "keywords": "software engineer",
  "location": "Spain",
  "jobsNumber": 100,
  "workModel": "remote",
  "fetchFullDetails": true
}

Filter by work model to analyze hiring patterns.

Tech Stack

• Apify SDK - Actor platform
• Bun - JavaScript runtime
• Cheerio - Fast HTML parsing
• Crawlee - Web scraping framework
• TypeScript - Type safety
• Zod - Data validation

License

ISC

Legal Notice

This tool is for legitimate data collection. Ensure compliance with LinkedIn's Terms of Service and GDPR regulations.