LinkedIn Profile & Company Data Extractor

An Apify Actor for extracting publicly available data from LinkedIn company pages and public profiles. Uses JSON-LD structured data, meta tags, and HTML parsing — no login required.

Features

Company Data Extraction

• Company Name — extracted from JSON-LD, meta tags, and HTML
• Industry — parsed from the company about page
• Company Size — employee count or size range
• Headquarters — location from about section
• Website — from JSON-LD sameAs or visible links
• Description — company summary
• Followers — follower count from interaction statistics
• Specialties — comma/semicolon-separated list

Profile Data Extraction

• Name & Headline — from JSON-LD Person schema, meta tags, HTML
• Location — geographic location
• About — profile summary text
• Experience — work history (company, title, dates, description)
• Education — schools, degrees, dates
• Connections Count — if publicly visible

Job Listing Extraction

• For each company, fetches job postings from LinkedIn's public jobs search
• Extracts: title, location, posted date, description, employment type
• Configurable limit (default 20, max 50)

Input

Field	Type	Default	Description
companyUrls	string[]	["https://www.linkedin.com/company/microsoft/"]	LinkedIn company page URLs
profileUrls	string[]	[]	LinkedIn public profile URLs
includeJobs	boolean	true	Whether to fetch job listings
maxJobs	integer	20	Max job listings per company (max 50)

Example Input

{
  "companyUrls": [
    "https://www.linkedin.com/company/microsoft/",
    "https://www.linkedin.com/company/google/"
  ],
  "profileUrls": [
    "https://www.linkedin.com/in/sundarpichai/"
  ],
  "includeJobs": true,
  "maxJobs": 10
}

Output

Each record is pushed to the Apify dataset. Records have a type field distinguishing companies from profiles.

Company Record Fields

Field	Type	Description
type	string	"company"
companyName	string	Company name
linkedinUrl	string	LinkedIn URL
slug	string	URL slug
industry	string	Industry
companySize	string	Employee count / range
headquarters	string	HQ location
website	string	Company website
description	string	Company description
followers	integer	LinkedIn followers
specialties	string[]	Specialty tags
jobs	object[]	Job listings (if requested)
scrapedAt	string	ISO 8601 timestamp

Profile Record Fields

Field	Type	Description
type	string	"profile"
name	string	Full name
headline	string	Profile headline
location	string	Location
about	string	About section
experience	object[]	Work experience
education	object[]	Education
connectionsCount	integer	Connection count
linkedinUrl	string	LinkedIn URL
scrapedAt	string	ISO 8601 timestamp

Job Entry Fields (inside jobs array)

Field	Type	Description
title	string	Job title
location	string	Job location
postedDate	string	Date posted
description	string	Job description
employmentType	string	Full-time, part-time, etc.
seniority	string	Seniority level

Technical Approach

1. JSON-LD — primary data source. Parse script[type="application/ld+json"] tags for Organization, Corporation, Person, and JobPosting schemas.
2. Meta tags — secondary source. Extract OG and standard meta tags.
3. Visible HTML — tertiary source. Regex patterns and CSS selectors for fields not in structured data.
4. Rate limiting — 3.5s delay between requests with exponential backoff on 429 responses.
5. Google Cache fallback — if the direct LinkedIn fetch fails, tries webcache.googleusercontent.com.
6. Graceful abort — listens for the Apify ABORTING event to stop mid-crawl.

Limitations

Important: LinkedIn is extremely protective of its data. This actor only extracts what is publicly visible without authentication. Many profiles and data fields require a LinkedIn login to access.

• Profile details (experience, education, about) are often only partially visible without login. Profiles with "public" visibility settings yield the most data.
• Job listings are fetched from the public jobs search page. Some companies may require login to view jobs.
• HTML selectors for experience/education sections are fragile — LinkedIn changes class names frequently. JSON-LD parsing is far more reliable.
• Rate limiting — aggressive scraping triggers LinkedIn's rate limits. The actor implements delays and backoff.
• No login/cookie support — this actor never authenticates. For authenticated scraping, consider using the Apify LinkedIn Actors with built-in session management.

Local Development

# Install dependencies
pip install -r requirements.txt

# Run locally with Apify CLI
apify run --purge

Deployment

$apify push

Input Schema

See .actor/input_schema.json for the full input specification.