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LinkedIn Scraper - Maximum Data Extraction 🚀

The most powerful LinkedIn Scraper on Apify — extract 50+ data fields from any LinkedIn page without login. This LinkedIn Scraper supports companies, profiles, job listings, job search, schools, events, and more. Get maximum data with zero configuration.

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⚡ Why This LinkedIn Scraper?

Most LinkedIn scrapers give you basic data — a name, a title, maybe a URL. This LinkedIn Scraper goes far beyond that. It extracts every piece of publicly available data from LinkedIn pages.

Feature	This LinkedIn Scraper	Other Scrapers
Company Data	50+ fields (tech stack, benefits, offices, employees, financials)	5-10 basic fields
Profile Data	40+ fields (skills, certifications, open-to-work status, languages)	Name + headline only
Job Data	40+ fields (salary, visa sponsorship, tech requirements, benefits)	Title + company only
Job Search	Parallel batch fetching with full detail extraction per job	Basic listing only
Login Required	❌ No login needed	✅ Most require cookies
Rate Limiting	Built-in smart delays + proxy support	Manual configuration

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🎯 3 Simple Scraping Modes

This LinkedIn Scraper offers three straightforward modes. Pick the one that fits your use case:

📎 URL Mode — Scrape Any LinkedIn Page

Paste one or more LinkedIn URLs and the LinkedIn Scraper automatically detects the page type and extracts all available data.

Supported URL types:

• /company/microsoft → Company pages
• /in/satyanadella → Profile pages
• /jobs/view/12345 → Job postings
• /posts/... → Posts
• /school/stanford-university → Schools & Universities
• /events/... → LinkedIn Events
• /learning/... → LinkedIn Learning courses
• /groups/... → Groups
• /feed/hashtag/python → Hashtag feeds
• /newsletters/... → Newsletters
• /company/.../products → Product pages
• /company/.../services → Service pages

Best for: Targeted scraping when you have specific LinkedIn URLs.

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🔍 Keyword Mode — Search Jobs by Keyword

Enter a keyword and the LinkedIn Scraper searches LinkedIn Jobs, then extracts detailed data for each result. Optionally filter by location.

Example keywords: python developer, data scientist, product manager, machine learning engineer

Best for: Job market research, salary benchmarking, competitive hiring analysis.

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🔗 Both Mode — URLs + Job Search Combined

Run URL scraping and job search in a single actor run. The LinkedIn Scraper processes your URLs first, then runs the keyword job search — all in one execution.

Best for: Comprehensive research combining company/profile data with job market data.

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🏢 Company Data — What You Get

When you scrape a company page with this LinkedIn Scraper, here is exactly what data you receive:

Core Company Information

• Company name — Official company name on LinkedIn
• Tagline — Company's short description line
• Industry — Primary industry classification (e.g., "Software Development")
• Company type — Public Company, Private, Nonprofit, etc.
• Employee count — Total number of employees (e.g., 228,327 for Microsoft)
• Follower count — LinkedIn followers (e.g., 27M+ for Microsoft)
• About / Description — Full company description text
• Website URL — Company website link
• LinkedIn URL — Direct LinkedIn company page URL
• Logo URL — High-resolution company logo image
• Headquarters — City and state of headquarters location
• Specialties — List of company specialties (e.g., "Cloud Computing", "AI", "Gaming")

Technology Stack

This LinkedIn Scraper detects the technologies mentioned on the company page — programming languages, cloud platforms, frameworks, databases, and tools. Example: ["Azure", "Python", "GitHub", "Next.js", "SQL Server"]

Benefits & Perks

The company benefits advertised on LinkedIn — healthcare, equity, PTO, EAP, laptop, and more. Example: ["Healthcare", "Equity", "PTO", "EAP", "Laptop"]

Office Locations

Every office the company has listed, with full address, country code, and map link. Includes street address, city, state, zip code, and country.

Affiliated Companies

All subsidiary and affiliated pages linked from the company — name, LinkedIn URL, industry classification, and location. For Microsoft, this includes GitHub, Xbox, Microsoft Azure, Microsoft Security, and more.

Similar Companies

Companies LinkedIn recommends as similar — name, URL, industry, and location. For Microsoft, this returns Google, Amazon, Meta, Netflix, LinkedIn, etc.

Employee Profiles

Key employees found on the company page — full name and LinkedIn profile URL. Includes executives, founders, and prominent team members.

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👤 Profile Data — What You Get

Scraping a LinkedIn profile with this LinkedIn Scraper gives you:

Identity & Professional Info

• Full name — Person's display name
• Title — Professional title from meta data (e.g., "Chairman and CEO at Microsoft")
• Headline — Full headline text with summary description
• Profile image — High-resolution profile photo URL
• Connections — Number of connections (500+ for most professionals)
• Location — Geographic location

Skills & Technology

• Technologies detected — Programming languages, frameworks, and tools mentioned (e.g., ["Azure", "GitHub", "GPT", "Phoenix"])
• Certifications detected — Professional certifications found (e.g., ["CFA"])

Career History

• Experience — Each position with job title, company name, duration, start/end dates, and whether it's a current role
• Awards — Honors and recognition mentioned
• Publications — Articles, reports, and annual reports authored
• Interests — Topics and areas of interest

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💼 Job Data — What You Get Per Job

Whether scraping a single job URL or searching by keyword, this LinkedIn Scraper extracts rich detail for every job posting:

Job Basics

• Title — Job title (e.g., "Python Developer")
• Company name — Hiring company
• Company URL — LinkedIn company page link
• Company logo — Company logo image URL
• Location — Full location with city and state (e.g., "Austin, TX")
• City, State, Country — Separated location fields
• Job URL — Direct link to the job posting
• Job image — Job listing image

Dates & Timing

• Posted date — Exact ISO date when posted (e.g., "2026-02-24T14:45:52.000Z")
• Posted ago — Human-readable relative time (e.g., "6 days ago")
• Application deadline — Deadline date when available

Compensation

• Salary minimum — Lower salary bound (e.g., $60,000)
• Salary maximum — Upper salary bound (e.g., $135,000)
• Salary currency — Currency code (e.g., "USD")
• Salary unit — Pay period (e.g., "YEAR")

Job Classification

• Seniority level — Entry level, Mid-Senior level, Director, VP, etc.
• Employment type — Full-time, Part-time, Contract, Internship
• Work location type — TELECOMMUTE for remote jobs
• Job function — Engineering, Information Technology, etc.
• Industry — Primary industry classification
• Industries list — All relevant industries

Requirements

• Experience years — Required years of experience (e.g., 6)
• Experience months — Required months of experience (e.g., 72)
• Education required — Degree level needed (e.g., "bachelor degree")
• Full description — Complete job description in HTML format

Application Info

• Applicants count — Number of people who applied (e.g., 200)
• Benefits snippet — Quick highlight (e.g., "Actively Hiring")

Technology Stack Detected

This LinkedIn Scraper analyzes the job description and extracts every technology mentioned — programming languages, frameworks, cloud platforms, databases, DevOps tools. Example: ["Python", "Django", "Docker", "Kubernetes", "AWS", "Kafka", "Elasticsearch"]

Benefits & Perks Found

All benefits mentioned in the job listing — medical, dental, vision, PTO, remote work, equity, disability insurance, wellness stipends, and more. Example: ["Dental", "Disability Insurance", "Paid Time Off", "Sick Leave"]

Similar Jobs

Up to 10 related job recommendations — each with title and direct LinkedIn URL. Useful for discovering similar opportunities.

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🔍 Job Search — How It Works

The job search mode in this LinkedIn Scraper is engineered for speed and completeness:

1. Search Phase — Fetches job listings from LinkedIn's search results pages
2. Detail Phase — Fetches full details for each job in parallel batches of 15
3. Enrichment — Merges search data with full job page data for maximum fields

Search Output Includes

• Keyword — The search term used
• Location — Location filter applied (if any)
• Limit — Maximum jobs requested
• Total found — Actual number of jobs extracted
• Jobs array — Full job data with all 40+ fields per job (as described above)
• Stats — Aggregate statistics:
  • Total pages fetched
  • Jobs with salary information
  • Remote jobs count

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🏫 Additional URL Types

This LinkedIn Scraper also handles these LinkedIn page types:

Schools & Universities

School name, description, follower count, alumni count, academic programs, degree types, notable alumni, campus locations, and affiliated institutions.

Events

Event name, description, date/time, organizer, attendee count, event format (online/in-person), speakers, and registration details.

LinkedIn Learning Courses

Course title, instructor name, duration, skill level, skills covered, number of learners, course description, and related courses.

Groups

Group name, description, member count, visibility (public/private), rules, admins, and recent activity.

Hashtags

Hashtag name, follower count, trending posts, top contributors, and related hashtags.

Newsletters

Newsletter name, author, subscriber count, publishing frequency, recent articles, and topics covered.

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📊 Input Configuration

Field	Description	Used In
Scraping Mode	Choose URL, Keyword, or Both mode	All modes
LinkedIn URLs	Paste LinkedIn URLs to scrape (auto-detects page type)	URL & Both modes
Job Search Keyword	Enter a job title or keyword to search	Keyword & Both modes
Job Location	Optional: filter by city, country, or "Remote"	Keyword & Both modes
Job Search Limit	Max number of jobs to fetch (1-1000)	Keyword & Both modes

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💡 Use Cases for This LinkedIn Scraper

Recruiters & Hiring Teams

Use this LinkedIn Scraper to monitor competitors' job postings, track hiring trends, and discover talent pools. The technology stack detection reveals exactly what skills companies are hiring for.

Market Researchers

Extract company data at scale — employee counts, technology stacks, office locations, affiliated companies, and industry classifications. Build competitive intelligence dashboards from real LinkedIn data.

Job Seekers

Search for jobs with full salary transparency, remote work availability, technology requirements, and benefits details. Compare opportunities across companies and locations with complete data.

Sales & Lead Generation

Build prospect lists from company pages with employee details, company size, industry, and technology stack information. Identify decision-makers and their professional backgrounds.

Data Analysts

Feed structured LinkedIn data into BI tools, machine learning models, or custom analytics pipelines. Every field is cleanly extracted and ready for analysis.

Academic Research

Study labor market trends, skill demand patterns, salary distributions, and company growth trajectories using rich, structured LinkedIn data.

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⚙️ Technical Details

• 4 Parallel Fetch Engines — Multiple independent engines work simultaneously for every request
• Browser Fingerprint Rotation — Each engine uses realistic browser signatures
• Smart Rate Limiting — Built-in delays prevent triggering LinkedIn's anti-bot systems
• Auto-Detection — Paste any LinkedIn URL and the scraper identifies the page type automatically
• Batch Processing — Job details fetched in parallel batches for maximum speed (12+ jobs/sec)
• Clean Output — All data is structured, deduplicated, and ready to use
• No Login Required — Works entirely with public data, no credentials needed

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🔒 Privacy & Compliance

This LinkedIn Scraper only extracts publicly available data — information that anyone can see without logging in. No authentication, cookies, or credentials are used or required.

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📬 Support

Questions about this LinkedIn Scraper? Need help with a specific use case? Reach out through the Apify platform — we're happy to help you get the most out of your LinkedIn data extraction.