LinkedIn Job Details Scraper 💼

Professional LinkedIn job scraper for extracting comprehensive job posting information. Get detailed insights from LinkedIn job listings including company info, requirements, benefits, and more.

🚀 Features

✅ Complete Job Data - Extract all job posting details
✅ Company Information - Get company name, logo, and LinkedIn profile
✅ Job Requirements - Full description, qualifications, and responsibilities
✅ Benefits & Perks - Comprehensive benefits information
✅ Application Data - Applicant count, posting date, and apply URLs
✅ Bulk Processing - Process multiple job postings at once

📤 Output Format

Each job posting returns comprehensive information:

{
  "id": "4165274290",
  "title": "Full Stack Engineer - TypeScript",
  "companyName": "MoonPay",
  "companyLinkedinUrl": "https://www.linkedin.com/company/moonpay",
  "companyLogo": "https://media.licdn.com/dms/image/...",
  "location": "Cracow, Małopolskie, Poland",
  "salaryInfo": [],
  "postedAt": "9 months ago",
  "benefits": [
    "Equity package",
    "Unlimited holidays",
    "Paid parental leave",
    "Annual training budget",
    "Home office setup allowance"
  ],
  "descriptionText": "Full job description...",
  "descriptionHtml": "<strong>Full HTML description...</strong>",
  "applicantsCount": "25",
  "seniorityLevel": "Not Applicable",
  "employmentType": "Full-time",
  "jobFunction": "Engineering and Information Technology",
  "industries": "Software Development",
  "link": "https://pl.linkedin.com/jobs/view/...",
  "scrapedAt": "2025-01-15T10:30:00.000Z",
  "status": "success"
}

📥 Input Format

Simply provide an array of LinkedIn job URLs:

{
  "jobUrls": [
    { "url": "https://linkedin.com/jobs/view/job-id-1234567890" },
    { "url": "https://linkedin.com/jobs/view/job-id-0987654321" },
    { "url": "https://linkedin.com/jobs/view/job-id-1122334455" }
  ]
}

🔧 How to Use

1. Collect URLs: Gather LinkedIn job posting URLs you want to scrape
2. Input URLs: Add them to the jobUrls array in the input
3. Run Actor: Click "Start" to begin processing
4. Export Data: Download results as CSV or JSON

📊 Data Fields Extracted

Basic Information

• Job ID and tracking information
• Job title and link
• Company name and LinkedIn profile
• Company logo URL
• Location details

Job Details

• Employment type (Full-time, Part-time, Contract, etc.)
• Seniority level
• Job function and industries
• Salary information (when available)

Content

• Full job description (text and HTML)
• List of benefits and perks
• Company description
• Requirements and qualifications

Metadata

• Number of applicants
• Posting date
• Application URL
• Scraping timestamp

🎯 Use Cases

Job Market Research: Analyze job trends, salaries, and requirements
Recruitment Intelligence: Monitor competitor job postings
Career Planning: Research job requirements and benefits
Data Analysis: Build datasets for job market analysis
Automation: Integrate with hiring workflows and ATS systems
Competitive Analysis: Track hiring patterns in your industry

⚡ Performance

• Processing Speed: ~3-5 seconds per job posting
• Success Rate: 95%+ for valid URLs
• Data Completeness: 90%+ fields populated
• Bulk Capacity: Process multiple jobs concurrently

🛡️ Best Practices

1. Valid URLs: Ensure URLs are complete LinkedIn job posting URLs
2. Rate Limiting: Built-in 2-second delay between requests
3. Error Handling: Failed jobs are logged with error details
4. Data Quality: Results include success/error status for each job

📋 URL Format Requirements

Valid LinkedIn job URLs should follow this format:

https://[country].linkedin.com/jobs/view/[job-title]-at-[company]-[job-id]

Examples:

• https://www.linkedin.com/jobs/view/1234567890
• https://pl.linkedin.com/jobs/view/engineer-at-company-1234567890
• https://uk.linkedin.com/jobs/view/manager-role-9876543210

🚫 Invalid URLs

The actor will reject:

• Non-LinkedIn URLs
• LinkedIn profile URLs
• LinkedIn company pages
• Malformed or incomplete URLs

📊 Statistics & Monitoring

The actor provides:

• Real-time progress logging
• Success/error counts
• Processing statistics
• Summary report in key-value store

🔍 Error Handling

When a job fails to scrape, the output includes:

{
  "originalUrl": "https://linkedin.com/jobs/view/...",
  "status": "error",
  "error": "Error message",
  "errorType": "HTTP 404",
  "scrapedAt": "2025-01-15T10:30:00.000Z"
}

💡 Tips for Best Results

1. Use Fresh URLs: Recent job postings have better success rates
2. Batch Processing: Process 10-50 jobs per run for optimal performance
3. Monitor Results: Check the overview dataset view for quick insights
4. Export Data: Use CSV format for easy analysis in spreadsheets

🔧 Technical Details

Webhook Integration: Connects to n8n webhook for data processing
Rate Limiting: 2-second delay between requests
Timeout: 60-second timeout per job
Error Recovery: Continues processing on individual failures
Data Storage: Results stored in Apify dataset with multiple views

📞 Support

Need help or have questions?

• Check the actor logs for detailed processing information
• Review error messages for troubleshooting
• Contact support for technical issues

🎁 More Tools

Looking for more LinkedIn automation tools? Check out our other scrapers for profiles, companies, and more!

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Ready to extract LinkedIn job data? Start scraping today! 🚀