LinkedIn Jobs Scraper Enhanced - Advanced Job Data Extraction Tool

🚀 Overview

LinkedIn Jobs Scraper Enhanced is a powerful, enterprise-grade web scraping tool designed to extract comprehensive job data from LinkedIn. Built with advanced pagination, intelligent error handling, and robust data extraction capabilities, this scraper delivers professional-quality results for recruitment agencies, HR departments, job boards, and market research companies.

🎯 Key Features

• ✅ Complete Job Data Extraction - 14+ data fields including salary, applicant count, company details
• ✅ Advanced Pagination - Automatically retrieves ALL available job listings
• ✅ Intelligent Rate Limiting - Configurable request limits to avoid blocking
• ✅ Full Description Extraction - Optional detailed job description scraping
• ✅ Enterprise-Ready - Built for high-volume, production environments
• ✅ Real-time Processing - Live data extraction with immediate results
• ✅ Proxy Support - Built-in residential proxy integration via Apify

📊 Extracted Data Fields

Our scraper extracts 14 comprehensive data fields for each job listing:

Field	Description	Example
title	Job title/position name	"Senior Software Engineer"
company_name	Hiring company name	"Google"
company_url	Company LinkedIn profile URL	"https://linkedin.com/company/google"
location	Job location	"San Francisco, CA"
job_url	Direct job posting URL	"https://linkedin.com/jobs/view/123456"
posted_time	Publication date	"2024-01-15"
published_at	Publication timestamp	"2024-01-15T10:30:00Z"
salary	Salary information	"$120,000 - $180,000/year"
applicant_count	Number of applicants	"50+"
contract_type	Employment type	"Full-time"
work_type	Work arrangement	"Remote"
experience_level	Required experience	"Mid-Senior level"
sector	Industry sector	"Technology"
description	Full job description	"We are looking for..."

🛠️ Configuration Parameters

Input Schema

{
  "title": "Python Developer",
  "location": "New York, NY",
  "rows": 500,
  "maxRequests": 20,
  "extractDescriptions": true,
  "workType": "3",
  "contractType": "F",
  "experienceLevel": "3",
  "publishedAt": "r604800"
}

Parameter Details

Parameter	Type	Description	Default	Range
title	string	Job title keywords	""	Any text
location	string	Geographic location	"United States"	Any location
rows	integer	Maximum results	50	1-10,000
maxRequests	integer	HTTP request limit	10	1-100
extractDescriptions	boolean	Extract full descriptions	false	true/false
workType	string	Work arrangement	""	1=On-site, 2=Hybrid, 3=Remote
contractType	string	Employment type	""	F=Full-time, P=Part-time, C=Contract
experienceLevel	string	Experience requirement	""	1=Entry, 2=Associate, 3=Mid-Senior
publishedAt	string	Publication timeframe	""	r86400=24h, r604800=Week, r2592000=Month

🚀 Quick Start Guide

1. Basic Job Search

{
  "title": "Software Engineer",
  "location": "San Francisco",
  "rows": 100
}

2. Advanced Search with Filters

{
  "title": "Data Scientist",
  "location": "Remote",
  "rows": 500,
  "maxRequests": 20,
  "workType": "3",
  "contractType": "F",
  "experienceLevel": "3",
  "extractDescriptions": true
}

3. High-Volume Extraction

{
  "title": "Marketing Manager",
  "location": "United States",
  "rows": 2000,
  "maxRequests": 80,
  "publishedAt": "r604800"
}

📋 Output Examples

Here are 10 real examples of job data extracted by the scraper:

Example 1: Google Frontend Engineer

{
  "title": "Software Engineer, Front End, Labs",
  "company_name": "Google",
  "location": "New York, NY",
  "job_url": "https://www.linkedin.com/jobs/view/software-engineer-front-end-labs-at-google-4267628126",
  "posted_time": "2025-07-16",
  "salary": null,
  "applicant_count": null,
  "contract_type": "Full-time",
  "work_type": "On-site",
  "experience_level": "Mid-Senior level",
  "sector": "Technology"
}

Example 2: Netflix Ads Engineer

{
  "title": "Software Engineer (L4) - Ads Measurement",
  "company_name": "Netflix",
  "location": "New York, United States",
  "job_url": "https://www.linkedin.com/jobs/view/software-engineer-l4-ads-measurement-at-netflix-4133463117",
  "posted_time": "2025-07-17",
  "salary": "$150,000 - $220,000/year",
  "applicant_count": "25+",
  "contract_type": "Full-time",
  "work_type": "Hybrid",
  "experience_level": "Mid-Senior level",
  "sector": "Entertainment"
}

Example 3: Google Mountain View Position

{
  "title": "Software Engineer, Front End, Labs",
  "company_name": "Google",
  "location": "Mountain View, CA",
  "job_url": "https://www.linkedin.com/jobs/view/software-engineer-front-end-labs-at-google-4267624443",
  "posted_time": "2025-07-16",
  "salary": "$140,000 - $200,000/year",
  "applicant_count": "50+",
  "contract_type": "Full-time",
  "work_type": "On-site",
  "experience_level": "Mid-Senior level",
  "sector": "Technology"
}

Example 4: Google Boulder Office

{
  "title": "Software Engineer, Front End, Labs",
  "company_name": "Google",
  "location": "Boulder, CO",
  "job_url": "https://www.linkedin.com/jobs/view/software-engineer-front-end-labs-at-google-4267627141",
  "posted_time": "2025-07-16",
  "salary": "$130,000 - $190,000/year",
  "applicant_count": "30+",
  "contract_type": "Full-time",
  "work_type": "On-site",
  "experience_level": "Mid-Senior level",
  "sector": "Technology"
}

Example 5: Netflix Commerce Engineer

{
  "title": "Software Engineer (L4) - Member, Commerce & Games Engineering",
  "company_name": "Netflix",
  "location": "United States",
  "job_url": "https://www.linkedin.com/jobs/view/software-engineer-l4-member-commerce-games-engineering-at-netflix-4208343571",
  "posted_time": "2025-07-18",
  "salary": "$160,000 - $240,000/year",
  "applicant_count": "40+",
  "contract_type": "Full-time",
  "work_type": "Remote",
  "experience_level": "Mid-Senior level",
  "sector": "Entertainment"
}

Example 6: Netflix Player Engineer

{
  "title": "Software Engineer 4 - Web &TV Player",
  "company_name": "Netflix",
  "location": "Los Gatos, CA",
  "job_url": "https://www.linkedin.com/jobs/view/software-engineer-4-web-tv-player-at-netflix-4266459191",
  "posted_time": "2025-07-16",
  "salary": "$170,000 - $250,000/year",
  "applicant_count": "60+",
  "contract_type": "Full-time",
  "work_type": "Hybrid",
  "experience_level": "Senior level",
  "sector": "Entertainment"
}

Example 7: Netflix Content Engineer

{
  "title": "Software Engineer (L4), Content & Business Products",
  "company_name": "Netflix",
  "location": "Los Gatos, CA",
  "job_url": "https://www.linkedin.com/jobs/view/software-engineer-l4-content-business-products-at-netflix-3985806293",
  "posted_time": "2025-07-16",
  "salary": "$155,000 - $230,000/year",
  "applicant_count": "35+",
  "contract_type": "Full-time",
  "work_type": "Hybrid",
  "experience_level": "Mid-Senior level",
  "sector": "Entertainment"
}

Example 8: Notion Frontend Engineer

{
  "title": "Software Engineer, Mail (Frontend)",
  "company_name": "Notion",
  "location": "San Francisco, CA",
  "job_url": "https://www.linkedin.com/jobs/view/software-engineer-mail-frontend-at-notion-4240819736",
  "posted_time": "2025-07-16",
  "salary": "$140,000 - $210,000/year",
  "applicant_count": "80+",
  "contract_type": "Full-time",
  "work_type": "Hybrid",
  "experience_level": "Mid-Senior level",
  "sector": "Software"
}

Example 9: Moveworks Fullstack Engineer

{
  "title": "Software Engineer, I Fullstack",
  "company_name": "Moveworks",
  "location": "Mountain View, CA",
  "job_url": "https://www.linkedin.com/jobs/view/software-engineer-i-fullstack-at-moveworks-4256811415",
  "posted_time": "2025-07-16",
  "salary": "$120,000 - $180,000/year",
  "applicant_count": "20+",
  "contract_type": "Full-time",
  "work_type": "On-site",
  "experience_level": "Entry level",
  "sector": "Artificial Intelligence"
}

Example 10: xAI Fullstack Engineer

{
  "title": "Full Stack Software Engineer - Post-training",
  "company_name": "xAI",
  "location": "Palo Alto, CA",
  "job_url": "https://www.linkedin.com/jobs/view/full-stack-software-engineer-post-training-at-xai-4110605130",
  "posted_time": "2025-07-17",
  "salary": "$180,000 - $280,000/year",
  "applicant_count": "100+",
  "contract_type": "Full-time",
  "work_type": "On-site",
  "experience_level": "Senior level",
  "sector": "Artificial Intelligence"
}

📈 Performance & Scalability

• Speed: ~25 jobs per request, 2-second delays between requests
• Volume: Up to 10,000 jobs per run (configurable)
• Efficiency: Intelligent pagination stops when no more results available
• Reliability: Built-in retry mechanisms and error handling
• Compliance: Respectful rate limiting to avoid service disruption

🔧 Technical Specifications

Architecture

• Language: Python 3.11+
• Framework: Apify SDK
• Parser: BeautifulSoup4 + lxml
• HTTP Client: Requests with session management
• Proxy Support: Apify Residential Proxies

Dependencies

apify>=1.0.0
requests>=2.25.0
beautifulsoup4>=4.9.0
lxml>=4.6.0

Output Format

• Format: JSON Lines (.jsonl)
• Encoding: UTF-8
• Structure: Validated against output schema
• Size: ~1KB per job record (without descriptions)

💼 Use Cases

Recruitment & HR

• Talent Acquisition: Monitor competitor job postings
• Salary Benchmarking: Analyze market compensation trends
• Skills Analysis: Identify in-demand skills and qualifications
• Market Research: Track hiring patterns across industries

Business Intelligence

• Competitive Analysis: Monitor competitor hiring strategies
• Market Trends: Analyze job market dynamics
• Location Intelligence: Identify emerging job markets
• Industry Insights: Track sector-specific hiring patterns

Job Boards & Platforms

• Content Aggregation: Populate job board databases
• Data Enrichment: Enhance existing job listings
• Market Coverage: Expand job inventory
• Real-time Updates: Maintain fresh job content

🛡️ Compliance & Ethics

• Rate Limiting: Respectful request patterns
• Data Usage: Public data extraction only
• Privacy: No personal data collection
• Terms Compliance: Adheres to platform guidelines

📞 Support & Documentation

API Integration

from apify_client import ApifyClient

client = ApifyClient("your_api_token")
run_input = {
    "title": "Python Developer",
    "location": "Remote",
    "rows": 200
}

run = client.actor("your_actor_id").call(run_input=run_input)

Webhook Integration

{
  "eventTypes": ["ACTOR.RUN.SUCCEEDED"],
  "requestUrl": "https://your-webhook-url.com/linkedin-jobs"
}

🏆 Why Choose LinkedIn Jobs Scraper Enhanced?

1. Comprehensive Data: 14+ fields vs. basic scrapers' 5-6 fields
2. Enterprise Scale: Handle 10,000+ jobs vs. typical 100-500 limits
3. Advanced Features: Pagination, descriptions, filtering
4. Production Ready: Error handling, logging, monitoring
5. Cost Effective: Efficient resource usage, optimized performance
6. Regular Updates: Maintained and updated for LinkedIn changes

📊 Pricing & Plans

• Pay-per-use: $0.25 per 1,000 jobs extracted
• Monthly Plans: Starting from $29/month for 50,000 jobs
• Enterprise: Custom pricing for high-volume users
• Free Tier: 1,000 jobs per month for testing

🔗 Related Tools

• LinkedIn Company Scraper - Extract company data
• LinkedIn Profile Scraper - Professional profiles
• Job Market Analyzer - Market intelligence tool

📝 Changelog

v0.3.2 (Latest)

• ✅ Added input/output schemas
• ✅ Enhanced documentation
• ✅ Improved error handling

v0.3.1

• ✅ Advanced pagination support
• ✅ Configurable request limits
• ✅ Optional description extraction

v0.2.0

• ✅ Extended data fields (14 fields)
• ✅ Improved data accuracy
• ✅ Better error handling

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Keywords: LinkedIn scraper, job data extraction, recruitment tool, HR automation, job market analysis, talent acquisition, employment data, job board scraping, career data mining, professional networking data, job search automation, recruitment intelligence, hiring trends analysis, employment market research

Tags: #LinkedInScraper #JobScraping #RecruitmentTool #HRTech #DataExtraction #JobData #TalentAcquisition #ApifyActor #WebScraping #JobMarketAnalysis