LinkedIn Scraper: Profiles, Companies, Posts & Jobs

This LinkedIn scraper extracts public LinkedIn profiles, company pages, posts, comments and job listings from their URLs, without a LinkedIn account, without cookies and without a browser. Paste LinkedIn profile, company, post or job URLs, or a LinkedIn jobs search URL, and get clean LinkedIn data as JSON, CSV or Excel: names, headlines, work experience, education, company size, industry, headquarters, followers, post text, reactions, comments, job descriptions and salaries.

It works as a LinkedIn profile scraper, a LinkedIn company scraper, a LinkedIn post scraper and a LinkedIn jobs scraper in one Actor, and as a real-time LinkedIn data API with no login. Field names are flat and stable (li_profile_url, li_company_url, linkedin_post_url, linkedin_job_url), so results drop straight into a spreadsheet, CRM or database.

This Actor is an independent tool. It is not affiliated with, endorsed by or sponsored by LinkedIn Corporation. "LinkedIn" is a trademark of LinkedIn Corporation and is used here only to describe which public web pages the Actor reads.

What does this LinkedIn scraper do?

It reads the pages that LinkedIn serves to logged-out visitors and turns them into structured data:

• 👤 LinkedIn profiles: name, headline, About section, location, current and past positions, the work experience and education a member made public, and follower count.
• 🏢 LinkedIn company pages: the full About section (website, industry, company size, headquarters, founding year, type, specialties), office locations, follower count, logo, the employees featured on the page and similar companies.
• 📝 LinkedIn posts: text, author, publication date, post type, media, reaction and comment counts.
• 💬 LinkedIn comments: the first public comments of a post, with each commenter's name, headline and profile URL.
• 💼 LinkedIn jobs: job listings from any LinkedIn jobs search URL or from a company's open positions (title, company, location, date posted), and full job postings with description, employment type, seniority, industry, pay range when shown, applicants, Easy Apply and job poster.

Try it now: open the Input tab, keep the prefilled company and profile, and click Start. You get two results in a few seconds.

You provide the URLs: this Actor doesn't search for people, companies or posts. For jobs, paste a LinkedIn jobs search URL with your keywords, location and filters, and it returns the matching job listings. As an Apify Actor, it comes with API access, scheduling, monitoring, integrations (n8n, Make, Zapier, Google Sheets, webhooks) and export to JSON, CSV, Excel, XML or HTML.

Fast and cheap to run. Plain HTTP requests, no headless browser, and one request per profile, company or post. Recent posts, featured employees and comments come from the same page at no extra request. Job lists take one request per 10 jobs, plus one small request per job when you want its full details. See how much it costs to scrape LinkedIn.

What can you use LinkedIn data for?

• 🎯 Lead generation and CRM enrichment: turn a list of LinkedIn profile and company URLs into complete person and company records for your CRM.
• 🔎 Account research and market mapping: collect company firmographics (industry, headcount, headquarters, office locations) and find similar companies.
• 📣 Content and brand monitoring: track what a company or a public figure posts on LinkedIn, and how many reactions and comments each post gets.
• 🧑‍💼 Recruiting and talent research: read the public work history and education of candidates you already found, and see which roles competitors are hiring for and how they describe them.
• 📊 Job market intelligence: collect the jobs of a LinkedIn search for a role or a region, then compare titles, seniority, employment types, pay ranges and applicant counts over time.
• 📈 "Who's hiring" lead signals: a company that opens new positions is growing or has a new need. Track the open jobs of your target accounts, or a daily search for the roles your product serves, and hand the hiring companies to your sales team.
• 🔁 Pay per result: replace per-seat or credit-based LinkedIn data tools and pay only for the results you get.
• 🤖 AI agents and automations: call the real-time LinkedIn API from n8n, Make, Zapier, LangChain or your own backend, and get JSON back from every call.

What data can you extract from LinkedIn?

Every result has provenance fields plus the fields of one entity: a profile, a company, a post, a comment, a job, or an error. entity_type tells you which. Field names are flat snake_case: li_* names for people and companies, and linkedin_* names for posts, comments and jobs.

A field is omitted when the public page doesn't show it. The Actor never returns null or "" placeholders, and it never guesses or fills a value from another source. What you get for a person depends on that member's public-visibility settings: from a full CV down to a name and an About section.

Provenance fields in every result

Field	Description
entity_type	person, company, post, comment, job or error
operation	people.enrich, companies.enrich, posts.enrich, people.posts / companies.posts for the recent posts shown on a profile or company page, jobs.enrich for a job URL, jobs.search for a jobs search URL, companies.jobs for a company's open jobs
input	The value from your input (URL or handle) that led to this result
source_url	The LinkedIn page actually downloaded (for posts fetched without comments, the lightweight /embed/ page; for jobs, LinkedIn's public job page or list page). On INVALID_INPUT errors: the value as given
scraped_at	ISO 8601 timestamp of the extraction

LinkedIn profile data

entity_type: "person".

Field	Description
li_profile_id	Numeric LinkedIn member id
li_profile_url, li_profile_handle	Canonical profile URL and public identifier
full_name, first_name, last_name	Name
headline	Text shown under the name
summary	The About section
location, li_profile_country	Displayed location and ISO-2 country code
li_profile_image_url	Profile photo (signed URL that expires)
job_title, company_name, li_company_url	Current position
past_job_title, past_company_name, past_li_company_url	Most recent past position
experiences[]	title, company_name, li_company_url, location, date (for example "2000 - Present"), job_time_period (for example "26 years"), company_logo_url
has_more_experiences	true when the page says more positions exist
education[], school_name, li_school_url	school_name, li_school_url, degree_name, date
skills[]	{ "name": … }, when the member made skills public
languages[], volunteer_experiences[]	When public
li_number_followers, li_number_connections	Follower count, and the connection count as displayed (LinkedIn caps the display at 500+)

The Actor returns every experience, education and skill entry the public page shows, with no cap.

LinkedIn company data

entity_type: "company".

Field	Description
company_name, li_company_url, li_company_id	Name, canonical page URL, and numeric id when the page exposes it
tagline, description	Slogan and About text
website, domain	Website from the About section, and its hostname without www.
industry, industries[], specialties[]	Industry and specialties
type, founded_on	For example "Privately Held", and the founding year as a number
employees_range, number_employees	Company size bracket ("201-500") and the employee count on LinkedIn
headquarters, country, city, postal_code, geographic_area	Headquarters
locations[], number_of_locations	Office locations: address, street, city, geographic_area, postal_code, country
logo_url	Logo (signed URL that expires)
li_followers_count	Followers
li_employees_url, li_job_search_url	Links to the LinkedIn search of the company's employees (opening it needs a login) and to its jobs page
affiliates[]	Affiliated and showcase pages shown on the company page
featured_employees[]	Employees featured on the page (up to 4 for logged-out visitors), as employee rows (full_name, first_name, last_name, summary = headline, li_profile_url, profile_image_url)
similar_pages[]	Similar companies: { company_name, li_company_url }

LinkedIn post data

entity_type: "post".

Field	Description
linkedin_post_id, linkedin_post_url	Numeric activity id, and the canonical https://www.linkedin.com/feed/update/urn:li:activity:<id> URL. Pulse articles have no linkedin_post_id, and their linkedin_post_url is the /pulse/ URL
published_date	ISO 8601 date-time
content_text	Post text
linkedin_post_type	text, image, video, document, article, poll, repost, job, event or other
reaction_count, comment_count	Engagement counts, when shown (repost counts are not shown to logged-out visitors)
hyperlinks[], post_media_url[]	Links and media in the post
full_name, first_name, last_name, linkedin_profile_url	Author (member)
linkedin_original_post, linkedin_job_url	Original post of a repost, and shared job
author_type, company_name, linkedin_company_url, article_title	Extensions: author kind (person or company), author company page, and article title

LinkedIn comment data

entity_type: "comment", with comment_text, comment_time, comment_like_count, linkedin_comment_id, linkedin_comment_url, full_name, first_name, last_name, linkedin_profile_url, linkedin_profile_handle, linkedin_profile_picture, summary (the commenter's headline), and linkedin_post_url / linkedin_post_id (the parent post). Each field is filled when shown.

LinkedIn job data

entity_type: "job". A job from a job URL, or from a list with Include job details on, has every field its posting shows. A job row from a search or a company's open positions has the fields marked ✓ in the Row column.

Field	Row	Description
linkedin_job_id, linkedin_job_url	✓	Numeric job id and canonical https://www.linkedin.com/jobs/view/<id> URL
title	✓	Job title
company_name, linkedin_company_url	✓	Hiring company and its LinkedIn page
company_logo_url	✓	Company logo (extension; signed URL that expires)
linkedin_company_id		Numeric company id (string)
job_location	✓	Location as displayed, for example "Paris, Île-de-France, France"
posted_at	✓	Date the job was listed, YYYY-MM-DD (search results only, see the FAQ)
posted_time_ago	✓	Age as displayed, for example "2 weeks ago" (extension)
job_description		Full description, with line breaks and - list items
type, field		Employment type ("Full-time") and industry
seniority_level, job_function		Seniority level and job function (extensions)
salary, salary_min, salary_max, salary_currency, salary_period		Pay range as displayed, when the employer shows one, and parsed: 250000, 380000, "USD", "year" (extensions)
applicants, applicants_count		Applicants as displayed ("Over 200 applicants", extension), and the number when LinkedIn shows an exact count
easy_apply		true for LinkedIn Easy Apply, false when you apply on the company's site (extension)
closed		true when the job no longer accepts applications (extension)
profile_full_name, linkedin_profile_url, profile_headline		The person who posted the job, when LinkedIn shows one (about half of postings; headline is an extension)

Not shown to logged-out visitors, so never filled: skills, remote_allowed (the remote flag), linkedin_job_application_url (the external apply link), reposted_at, the poster's linkedin_profile_id, and posted_at on job pages, which only show an age such as "2 weeks ago".

Errors

An input that fails produces an error result (entity_type: "error"). The run doesn't crash, and the input is never silently dropped. The result has error_label and message:

error_label	Meaning
INVALID_INPUT	The value isn't a usable LinkedIn URL, or the page type is out of scope (school, directory, job collections)
NOT_FOUND	LinkedIn answered 404: the profile, company, post or job doesn't exist or was removed
BLOCKED	LinkedIn refused the page on every retry with a fresh IP. Try again later
INTERNAL_ERROR	Unexpected failure. Please report it in the Issues tab

Errors are never charged.

How to scrape LinkedIn profiles, companies and posts

1. Open the Actor's Input tab.
2. Paste LinkedIn profile, company and/or post URLs. For jobs, open the Jobs section (see how to scrape LinkedIn jobs).
3. Optionally turn on recent posts or comments in Options.
4. Click Start. Results appear in the Output tab while the run is going.
5. Download them as JSON, CSV, Excel, XML or HTML, send them to Google Sheets, or fetch them through the API.

You can combine profiles, companies, posts and jobs in one run. Each result says which operation and which input produced it.

How to scrape LinkedIn profiles

Paste profile URLs or public identifiers (the part after /in/):

{ "profileUrls": ["https://www.linkedin.com/in/williamhgates", "satyanadella"] }

How to scrape LinkedIn company pages and their posts

Paste company page URLs or universal names (the part after /company/). Turn on includeCompanyPosts to also get the recent posts shown on each company page:

{ "companyUrls": ["https://www.linkedin.com/company/apify", "microsoft"], "includeCompanyPosts": true }

How to scrape LinkedIn posts and comments

Paste post URLs in any form (/posts/…, /feed/update/…, /embed/…, /pulse/…) or bare activity ids. Turn on includeComments to also get the first public comments:

{
    "postUrls": ["https://www.linkedin.com/feed/update/urn:li:activity:7509678332976820224"],
    "includeComments": true
}

All input options

Field	Type	Default	What it does
profileUrls	string[]	[]	Profile URLs or public identifiers → person
companyUrls	string[]	[]	Company or showcase URLs, or universal names → company
postUrls	string[]	[]	/posts/…, /feed/update/urn:li:…, /embed/…, /pulse/… URLs or bare activity ids → post
includeProfilePosts	boolean	false	Also output the recent activity shown on profile pages (no extra request)
includeCompanyPosts	boolean	false	Also output the recent posts shown on company pages (no extra request)
includeComments	boolean	false	Use the full post page and output its public comments. false = light embed page, about 7× smaller
jobUrls	string[]	[]	Job URLs (/jobs/view/…, any URL with currentJobId=) or bare job ids → job with details
jobSearchUrls	string[]	[]	LinkedIn jobs search URLs or job listing pages → one job row per result
includeCompanyJobs	boolean	false	Also output the open jobs of each company in companyUrls
includeJobDetails	boolean	false	Download each listed job's page for its full details (+1 small request per job)
maxJobs	integer 1–1000	25	Max jobs per jobs search URL and per company. Job URLs are not limited
proxyConfiguration	proxy	Residential	Proxy for LinkedIn pages
maxConcurrency	integer 1–50	10	Parallel downloads
maxRequestRetries	integer 0–10	6	Retries on a fresh IP after a block

How to scrape LinkedIn jobs

The Actor reads the job pages that LinkedIn shows on linkedin.com/jobs to logged-out visitors. There are three ways in:

• Job URLs (jobUrls): each job comes back with its full details.
• Jobs search URLs (jobSearchUrls): one row per job (title, company, location, date posted), up to maxJobs per search.
• Company pages (companyUrls + includeCompanyJobs): the company's open positions, as rows.

Rows take one request per 10 jobs. Turn on includeJobDetails to also get the full posting of every row, for one more small request per job. A job that several searches or companies of the same run find is returned once.

How to get a LinkedIn jobs search URL

1. Open linkedin.com/jobs/search. You don't need to log in.
2. Enter keywords and a location, and set the filters you want, such as date posted, company or Easy Apply.
3. Copy the URL from the address bar and paste it into Jobs search URLs.

{ "jobSearchUrls": ["https://www.linkedin.com/jobs/search?keywords=Data%20Engineer&location=France"], "maxJobs": 100 }

A /jobs/search URL without a location covers the whole world, whatever the proxy's country. Job listing pages such as https://www.linkedin.com/jobs/data-engineer-jobs work too, but LinkedIn searches them in the location it picks for the page (for example the United States): to search another location, add location= to the URL (…/jobs/data-engineer-jobs?location=France) or use a /jobs/search URL. Only the search parameters of a URL are used (keywords, location, filters, distance and sort order); tracking and sign-in parameters, such as those of job-alert e-mails, are dropped. LinkedIn shows at most 1,000 results per search: to get more, split the search by location, date posted or another filter.

How to scrape all open jobs of a company

Put the company page in Company URLs and turn on includeCompanyJobs. The jobs come from the See jobs button of the company page, which also covers the pages LinkedIn groups under the company (for Microsoft, its subsidiaries). A company with no open jobs has no such button: you get the company and no jobs, and no extra request is made.

{ "companyUrls": ["https://www.linkedin.com/company/microsoft"], "includeCompanyJobs": true, "maxJobs": 50 }

The jobs have operation: "companies.jobs" and the company's input in input, so you can join them to the company.

How to get full job descriptions and salaries

Paste job URLs into Job URLs: https://www.linkedin.com/jobs/view/<id> with or without the title, any LinkedIn jobs URL with currentJobId=<id>, or bare job ids. For searches and companies, turn on includeJobDetails:

{
    "jobSearchUrls": ["https://www.linkedin.com/jobs/search?keywords=Software%20Engineer&location=United%20States"],
    "includeJobDetails": true,
    "maxJobs": 25
}

Each job then takes one more request to LinkedIn's public job page (about 25–80 KB) and is charged as a detailed job instead of a row. The salary fields are filled only when the employer shows a pay range. A job that no longer accepts applications is still returned, with closed: true; a job id that doesn't exist gives a NOT_FOUND error.

How to monitor new LinkedIn jobs every day

1. On LinkedIn, set Date posted to Past 24 hours. This adds f_TPR=r86400 to the search URL; you can also add it yourself.
2. Paste the URL into Jobs search URLs, set maxJobs to more than a day's worth of jobs, and save the input as a Task.
3. Schedule the task to run every day, and send the results to Google Sheets, Slack or a webhook with an integration.

{
    "jobSearchUrls": ["https://www.linkedin.com/jobs/search?keywords=Data%20Engineer&location=France&f_TPR=r86400"],
    "maxJobs": 200
}

Logged out, LinkedIn lists results in its own order and ignores the sort option (sortBy), so the filter, not the order, is what keeps each run to new jobs. Two runs a day apart can share a few jobs: deduplicate on linkedin_job_id.

How does it scrape LinkedIn without login?

1. Public pages only. The Actor downloads the same public pages that any logged-out visitor, or a search engine, sees: /in/<id>, /company/<name>, /posts/…, /feed/update/…, /embed/feed/update/…, /pulse/…, and the job pages and job search results that linkedin.com/jobs loads for logged-out visitors. It never logs in, never uses cookies or accounts, never solves captchas and never pretends to be a search-engine crawler.
2. HTTP only, no browser. Each page is one HTTP request with a real-browser TLS fingerprint. The page is parsed from its structured data (JSON-LD) first and then from stable HTML attributes. A page takes about a second and only a few milliseconds of CPU.
3. Residential proxy with automatic retry. LinkedIn blocks datacenter IPs quickly, so each request goes through an Apify Residential IP. When LinkedIn answers with its sign-in wall, an HTTP 999 or a 429, the Actor retries on a fresh IP (up to maxRequestRetries). Blocked answers are small, so retries cost little.
4. One request per profile, company or post. Recent posts, featured employees, similar pages and comments come from the same page. Posts requested without comments are read from LinkedIn's 24 KB embed page instead of the ~170 KB post page; the exact publication time is decoded from the post id. Jobs are read from LinkedIn's lightweight job pages: one request per 10 jobs of a list, and one 25–80 KB request per job with details instead of the 260–340 KB full job page.
5. Deduplication. Inputs that point to the same page (for example jbalada, JBalada and https://fr.linkedin.com/in/jbalada/) are downloaded and charged once; the first input is echoed in input. A job found by several searches or companies of the same run is output and charged once.

LinkedIn scraper output examples

The examples below are abbreviated. They were extracted from the public LinkedIn pages of Apify and Bill Gates on 2026-09-27, and from public LinkedIn job pages on 2026-09-28.

All result types share one dataset. Filter on entity_type. This is deliberate: run-sync-get-dataset-items and the Export button only return the default dataset, so one synchronous API call returns people, companies, posts, jobs and errors together. The Output tab views (People, Companies, Posts, Comments, Jobs, Job details, Errors) only choose columns. To filter results, use for example jq '.[] | select(.entity_type == "company")'.

LinkedIn company data example

{
    "entity_type": "company",
    "operation": "companies.enrich",
    "input": "https://www.linkedin.com/company/apify",
    "source_url": "https://www.linkedin.com/company/apify",
    "scraped_at": "2026-09-27T10:00:00.000Z",
    "company_name": "Apify",
    "li_company_url": "https://www.linkedin.com/company/apify",
    "tagline": "Thousands of Actors to automate your business, get real-time web data, and integrate your apps and agents.",
    "description": "Apify is the largest marketplace of tools for AI. More than 50,000 Actors to automate your business. …",
    "website": "https://apify.com/",
    "domain": "apify.com",
    "industry": "Technology, Information and Internet",
    "industries": ["Technology, Information and Internet"],
    "type": "Privately Held",
    "founded_on": 2016,
    "employees_range": "201-500",
    "number_employees": 272,
    "headquarters": "Prague",
    "country": "CZ",
    "city": "Prague",
    "postal_code": "11100",
    "specialties": [
        "Web scraping",
        "Browser automation",
        "AI agents",
        "API integration",
        "Data pipelines",
        "No-code tools",
        "Actor marketplace",
        "Developer platform"
    ],
    "locations": [
        {
            "address": "Vodickova 704/36 Prague, 11100, CZ",
            "street": "Vodickova 704/36",
            "city": "Prague",
            "postal_code": "11100",
            "country": "CZ"
        },
        { "address": "San Francisco, CA, US" }
    ],
    "number_of_locations": 2,
    "li_followers_count": 38579,
    "logo_url": "https://media.licdn.com/dms/image/v2/D4D0BAQF7OnC-r1njIA/company-logo_200_200/…",
    "similar_pages": [
        { "company_name": "n8n", "li_company_url": "https://www.linkedin.com/company/n8n" },
        { "company_name": "Make", "li_company_url": "https://www.linkedin.com/company/itsmakehq" }
    ]
}

LinkedIn profile data example

{
    "entity_type": "person",
    "operation": "people.enrich",
    "input": "https://www.linkedin.com/in/williamhgates",
    "source_url": "https://www.linkedin.com/in/williamhgates",
    "scraped_at": "2026-09-27T10:00:00.000Z",
    "li_profile_handle": "williamhgates",
    "li_profile_url": "https://www.linkedin.com/in/williamhgates",
    "full_name": "Bill Gates",
    "first_name": "Bill",
    "last_name": "Gates",
    "headline": "Chair, Gates Foundation and Founder, Breakthrough Energy",
    "summary": "Chair of the Gates Foundation. Founder of Breakthrough Energy. Co-founder of Microsoft. Voracious reader. Avid traveler. Active blogger.",
    "location": "Seattle, Washington, United States",
    "li_profile_country": "US",
    "li_profile_image_url": "https://media.licdn.com/dms/image/v2/D5603AQF-RYZP55jmXA/profile-displayphoto-shrink_200_200/…",
    "job_title": "Co-chair",
    "company_name": "Gates Foundation",
    "li_company_url": "https://www.linkedin.com/company/gates-foundation",
    "li_number_followers": 40683385,
    "experiences": [
        {
            "title": "Co-chair",
            "company_name": "Gates Foundation",
            "li_company_url": "https://www.linkedin.com/company/gates-foundation",
            "date": "2000 - Present",
            "job_time_period": "26 years"
        },
        {
            "title": "Founder",
            "company_name": "Breakthrough Energy",
            "li_company_url": "https://www.linkedin.com/company/breakthrough-energy",
            "date": "2015 - Present",
            "job_time_period": "11 years"
        },
        {
            "title": "Co-founder",
            "company_name": "Microsoft",
            "li_company_url": "https://www.linkedin.com/company/microsoft",
            "date": "1975 - Present",
            "job_time_period": "51 years"
        }
    ],
    "education": [
        {
            "school_name": "Harvard University",
            "li_school_url": "https://www.linkedin.com/school/harvard-university",
            "date": "1973 - 1975"
        },
        { "school_name": "Lakeside School" }
    ],
    "school_name": "Harvard University",
    "li_school_url": "https://www.linkedin.com/school/harvard-university"
}

LinkedIn post data example

{
    "entity_type": "post",
    "operation": "posts.enrich",
    "input": "https://www.linkedin.com/feed/update/urn:li:activity:7509678332976820224",
    "source_url": "https://www.linkedin.com/embed/feed/update/urn:li:activity:7509678332976820224",
    "scraped_at": "2026-09-27T10:00:00.000Z",
    "linkedin_post_id": "7509678332976820224",
    "linkedin_post_url": "https://www.linkedin.com/feed/update/urn:li:activity:7509678332976820224",
    "published_date": "2026-09-26T18:20:37.656Z",
    "content_text": "Hannah and her team at Our World in Data do an incredible job of putting the world’s progress into perspective—and showing just how much has changed for the better, even as we face real challenges. Worth the watch.",
    "linkedin_post_type": "video",
    "reaction_count": 452,
    "comment_count": 65,
    "full_name": "Bill Gates",
    "first_name": "Bill",
    "last_name": "Gates",
    "linkedin_profile_url": "https://www.linkedin.com/in/williamhgates",
    "author_type": "person"
}

LinkedIn comment data example

The commenter is anonymised in this example.

{
    "entity_type": "comment",
    "operation": "posts.enrich",
    "input": "https://www.linkedin.com/feed/update/urn:li:activity:7509678332976820224",
    "source_url": "https://www.linkedin.com/feed/update/urn:li:activity:7509678332976820224",
    "scraped_at": "2026-09-27T10:00:00.000Z",
    "linkedin_post_id": "7509678332976820224",
    "linkedin_post_url": "https://www.linkedin.com/feed/update/urn:li:activity:7509678332976820224",
    "full_name": "Jane Doe",
    "comment_text": "…",
    "comment_time": "2026-09-26T19:08:43.824Z",
    "comment_like_count": 7
}

LinkedIn job search row example

One row of a jobs search (jobSearchUrls, details off):

{
    "entity_type": "job",
    "operation": "jobs.search",
    "input": "https://www.linkedin.com/jobs/search?keywords=data%20engineer&location=France",
    "source_url": "https://www.linkedin.com/jobs-guest/jobs/api/seeMoreJobPostings/search?keywords=data+engineer&location=France&start=0",
    "scraped_at": "2026-09-28T10:00:00.000Z",
    "linkedin_job_id": 4446387035,
    "linkedin_job_url": "https://www.linkedin.com/jobs/view/4446387035",
    "title": "Senior Data Engineer - BeReal",
    "company_name": "BeReal.",
    "linkedin_company_url": "https://www.linkedin.com/company/bereal-app",
    "job_location": "Paris, Île-de-France, France",
    "posted_at": "2026-09-10",
    "posted_time_ago": "2 weeks ago",
    "company_logo_url": "https://media.licdn.com/dms/image/v2/C4D0BAQG16tpcM1rf-A/company-logo_100_100/…"
}

LinkedIn job details example

A job URL (jobUrls). A search job with includeJobDetails has the same fields, plus posted_at from its row:

{
    "entity_type": "job",
    "operation": "jobs.enrich",
    "input": "https://www.linkedin.com/jobs/view/4446500774",
    "source_url": "https://www.linkedin.com/jobs-guest/jobs/api/jobPosting/4446500774",
    "scraped_at": "2026-09-28T10:00:00.000Z",
    "linkedin_job_id": 4446500774,
    "linkedin_job_url": "https://www.linkedin.com/jobs/view/4446500774",
    "title": "Principal Software Engineer",
    "company_name": "Snowflake",
    "linkedin_company_url": "https://www.linkedin.com/company/snowflake-computing",
    "linkedin_company_id": "3653845",
    "job_location": "Bellevue, WA",
    "job_description": "At Snowflake, we are powering the era of the agentic enterprise. …\n\nWhat You Will Do\n\nAs a software engineer on the team, you will play a central role in delivering the next generation of tools and evolve our developer infrastructure and tooling to be scalable, highly performant, and AI-first.\n\n- Design and build AI-first platforms, tools, and best practices to significantly enhance the developer experience for Snowsight\n- …",
    "type": "Full-time",
    "field": "Software Development",
    "applicants": "118 applicants",
    "applicants_count": 118,
    "seniority_level": "Not Applicable",
    "job_function": "Engineering and Information Technology",
    "posted_time_ago": "2 weeks ago",
    "salary": "$250,000.00/yr - $380,000.00/yr",
    "salary_min": 250000,
    "salary_max": 380000,
    "salary_currency": "USD",
    "salary_period": "year",
    "easy_apply": false,
    "closed": false,
    "company_logo_url": "https://media.licdn.com/dms/image/v2/D560BAQF3mYS3WqCB3g/company-logo_100_100/…"
}

When LinkedIn shows the person who posted the job, the item also has profile_full_name, linkedin_profile_url and profile_headline.

Error example

{
    "entity_type": "error",
    "operation": "people.enrich",
    "input": "https://www.linkedin.com/in/this-profile-does-not-exist",
    "source_url": "https://www.linkedin.com/in/this-profile-does-not-exist",
    "scraped_at": "2026-09-27T10:00:00.000Z",
    "error_label": "NOT_FOUND",
    "message": "LinkedIn answered HTTP 404."
}

LinkedIn API alternative: call it from your code

LinkedIn's official APIs are reserved for approved partners and don't return public profile or company data for any URL you choose. This Actor gives you that data through the Apify API, in three ways. All of them authenticate with your Apify API token (Authorization: Bearer <APIFY_TOKEN>). In the examples, replace <username> with the username of the account that owns the Actor.

Synchronous API call: results in the response

Use this for small jobs, for example tens of URLs, when the run finishes in under 5 minutes. The response body is the list of results. Pass maxTotalChargeUsd to cap what a run can cost you.

curl -X POST "https://api.apify.com/v2/actors/<username>~linkedin-scraper/run-sync-get-dataset-items?maxTotalChargeUsd=0.50&clean=true" \
  -H "Authorization: Bearer $APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"companyUrls": ["https://www.linkedin.com/company/apify"], "profileUrls": ["williamhgates"]}'

Add &format=csv or &format=xlsx to get a CSV or Excel file instead of JSON. If a run takes longer than 300 seconds, the API answers 408. For larger jobs, use an asynchronous run.

Asynchronous runs for bulk LinkedIn scraping

# 1) Start the run (returns data.id and data.defaultDatasetId)
curl -X POST "https://api.apify.com/v2/actors/<username>~linkedin-scraper/runs?maxTotalChargeUsd=5" \
  -H "Authorization: Bearer $APIFY_TOKEN" -H "Content-Type: application/json" \
  -d @input.json

# 2) Wait for it (repeat until status is SUCCEEDED), or register a webhook on ACTOR.RUN.SUCCEEDED
curl "https://api.apify.com/v2/actor-runs/<RUN_ID>?waitForFinish=60" -H "Authorization: Bearer $APIFY_TOKEN"

# 3) Download the results
curl "https://api.apify.com/v2/datasets/<DATASET_ID>/items?clean=true&format=json" -H "Authorization: Bearer $APIFY_TOKEN"

Scrape LinkedIn with Python

from apify_client import ApifyClient

client = ApifyClient("<APIFY_TOKEN>")
run = client.actor("<username>/linkedin-scraper").call(
    run_input={"profileUrls": ["https://www.linkedin.com/in/williamhgates"], "companyUrls": ["apify"]}
)
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item["entity_type"], item.get("full_name") or item.get("title") or item.get("company_name"))

Scrape LinkedIn with JavaScript and Node.js

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('<username>/linkedin-scraper').call({ profileUrls: ['williamhgates'] });
const { items } = await client.dataset(run.defaultDatasetId).listItems();

Real-time LinkedIn API (Standby endpoints)

The Actor also runs as a web server (Apify Standby mode) at https://<username>--linkedin-scraper.apify.actor. Each endpoint takes one LinkedIn URL and returns JSON: a profile, company, post or job in about a second, and a list of jobs a little later (one request per 10 jobs). Errors come back as a JSON body with error_label, message and status_code. Status codes: 400 (bad or out-of-scope URL), 402 (LIMIT_REACHED: the run's maximum cost was reached), 404 (unknown endpoint or LinkedIn 404), 405 (not a GET), 502 (BLOCKED), 500, and 504 (TIMEOUT: no answer within 240 s). A call is charged only after its answer has been sent. If you disconnect first, the Actor stops waiting, starts no further attempt and charges nothing. The Endpoints tab has an interactive OpenAPI console.

curl -G "https://<username>--linkedin-scraper.apify.actor/v1/people/enrich" \
  -H "Authorization: Bearer $APIFY_TOKEN" \
  --data-urlencode "li_profile_url=https://www.linkedin.com/in/williamhgates"

curl -G "https://<username>--linkedin-scraper.apify.actor/v1/companies/enrich" \
  -H "Authorization: Bearer $APIFY_TOKEN" --data-urlencode "li_company_url=https://www.linkedin.com/company/apify"

curl -G "https://<username>--linkedin-scraper.apify.actor/v1/posts/enrich" \
  -H "Authorization: Bearer $APIFY_TOKEN" \
  --data-urlencode "li_post_url=https://www.linkedin.com/feed/update/urn:li:activity:7509678332976820224" \
  --data-urlencode "include_comments=true"

curl -G "https://<username>--linkedin-scraper.apify.actor/v1/jobs/enrich" \
  -H "Authorization: Bearer $APIFY_TOKEN" --data-urlencode "li_job_url=https://www.linkedin.com/jobs/view/4446500774"

curl -G "https://<username>--linkedin-scraper.apify.actor/v1/jobs/search" \
  -H "Authorization: Bearer $APIFY_TOKEN" \
  --data-urlencode "li_job_search_url=https://www.linkedin.com/jobs/search?keywords=Data%20Engineer&location=France" \
  --data-urlencode "page=1" --data-urlencode "page_size=50"

curl -G "https://<username>--linkedin-scraper.apify.actor/v1/companies/enrich" \
  -H "Authorization: Bearer $APIFY_TOKEN" --data-urlencode "li_company_url=https://www.linkedin.com/company/apify" \
  --data-urlencode "include_jobs=true" --data-urlencode "max_jobs=25"

Endpoint	Parameters	Returns
GET /v1/people/enrich	li_profile_url (required), include_posts	Person (+ posts)
GET /v1/companies/enrich	li_company_url (required), include_posts, include_jobs, max_jobs (1–100, default 25), include_job_details	Company (+ posts, jobs)
GET /v1/posts/enrich	li_post_url (required), include_comments	Post (+ comments)
GET /v1/jobs/enrich	li_job_url (required; or linkedin_job_url)	Job with details
GET /v1/jobs/search	li_job_search_url (required; or linkedin_job_search_url), page (from 1), page_size (10–100 in steps of 10, default 50), max_results (1–100), include_job_details	Array of jobs

/v1/jobs/search is paged: request page=1, 2, … until you get [], which means past the last result or past LinkedIn's limit of 1,000 results per search. To get just the first jobs in one call, pass max_results=n (any number from 1 to 100) instead of page_size. With include_jobs=true, a company without open jobs gets "jobs": [].

Standby runs start on demand and stay warm between calls. A profile, company, post or job call is a single direct page download (a live test answered a post-with-comments call in 0.5 s). Job lists fetch up to 5 pages at a time within the 240 s budget. When a result is partial, on any endpoint (job-list pages blocked or failing on every retry, out of time, or posts, comments or jobs left out because the run's maximum cost was reached), the call still answers 200 with what it has and sets the headers X-Results-Incomplete: true and X-Results-Incomplete-Reason (blocked, error, timeout or budget). The maximum cost is checked before anything is downloaded: a call the run can't pay for answers 402 without any request to LinkedIn, and a job list stops at the jobs the run can still pay for. The first call after an idle period also waits a few seconds for a run to start. GET / lists the endpoints. There are no credits or plan quotas: the only limits are Apify's (2,000 requests/s per account for Standby) and the run's maximum cost.

How does it compare with other ways to get LinkedIn data?

	This LinkedIn scraper	LinkedIn official API	Cookie-based scrapers
Needs a LinkedIn account or cookies	No	Partner approval	Yes, your session cookie
Risk to your LinkedIn account	None	None	Restriction or ban
Any public profile, company or job URL	Yes	No	Yes
People search, employee lists, emails	No	Limited	Often
Pricing	Pay per result, no subscription	Partner agreement	Varies
Real-time API	Yes (Standby)	Yes	Rarely

Choose this Actor when you already have the LinkedIn URLs, or a LinkedIn jobs search, and want their public data cheaply and without risking an account.

What this LinkedIn scraper can't do

It only sees what logged-out visitors see:

• No people, company or content search. You provide the URLs; the Actor doesn't search LinkedIn or search engines for them. LinkedIn jobs search URLs that you paste are supported.
• Jobs: at most 1,000 results per search, in LinkedIn's order. Job pages show no skills, remote flag, application link or posting date to logged-out visitors (search results carry the date).
• No full employee lists. You get the employees featured on the company page (up to 4) and li_employees_url, the LinkedIn search that lists them, which needs a login to open.
• Only the first public comments (usually about 10 per post) and no lists of reactions: you get the reaction count only.
• Short post history. A company page shows about 10 recent posts, and a profile only its few most recent activity items. Older posts aren't shown to logged-out visitors.
• Hidden profile sections stay hidden. Members choose what logged-out visitors see. Skills, languages and certifications are often private. The Actor never fills hidden fields from other sources.
• No emails or phone numbers. LinkedIn doesn't show contact details to logged-out visitors.
• Out of scope: school pages (/school/…), the public directory (/pub/dir/…), activity feeds (/in/…/recent-activity/…, which is read as the profile itself) and job collections (/jobs/collections/…). LinkedIn blocks these for logged-out visitors anyway.
• Image URLs expire. LinkedIn image URLs are signed. Download photos or logos promptly if you need to keep them.
• Typical success rates after automatic retries (estimates based on public reports, not guarantees) are roughly 85–95 % for profiles, which are the most protected pages, and higher for company pages and posts. Failures are reported as BLOCKED errors, never as empty results, and are not charged. Re-running the failed inputs later usually succeeds.

How much does it cost to scrape LinkedIn?

You pay per result, with no subscription. Failed and blocked pages are free.

Result	Event	Price per 1,000 results
LinkedIn profile	person	$3.50
LinkedIn company page	company	$3.00
LinkedIn post	post	$1.50
LinkedIn comment	comment	$0.50
LinkedIn job with details	job	$1.00
LinkedIn job row (search or company list, no details)	job_card	$0.30

Bronze, Silver and Gold subscribers pay less: see the Pricing tab. Always pass maxTotalChargeUsd on API calls to cap your spend; the run stops cleanly when the cap is reached.

LinkedIn jobs: a full job posting (description, seniority, employment type, pay range when shown, applicants, job poster, Easy Apply or external, closed flag) costs $1.00 per 1,000, down to $0.70 on Gold. Rows from a job search or a company's open positions, without the description, cost $0.30 per 1,000 (down to $0.21). Each job is charged once: as a detailed job or as a row, never both. A row that is saved because its details couldn't be fetched costs the row price.

Example: 1,000 company pages cost $3.00. The same 1,000 companies with their recent posts (about 10 each) cost $3.00 + 10,000 × $0.0015 = $18.00. A jobs search of 1,000 results costs $0.30 as rows, or $1.00 with full details.

Is scraping LinkedIn free?

Apify's free plan includes $5 of credit every month, which covers about 1,400 LinkedIn profiles, 1,600 company pages, 4,900 full job postings or 16,000 job search rows a month with this Actor, at no cost.

Why it's cheap to run

Resource	Usage
Memory	512 MB by default (HTTP only, no browser). The allowed range is 256–1,024 MB
Time	About 0.7–1 second per page; 10 pages in parallel by default
Data per page (compressed)	Profile ≈ 120–170 KB, company ≈ 20–100 KB, full post ≈ 20–35 KB, embed post ≈ 5 KB, job list page (10 jobs) ≈ 3 KB, job details ≈ 6–10 KB
Storage	One dataset write per result. No screenshots, no HTML snapshots and no key-value store writes per result

Tips to make runs faster and cheaper

1. Leave includeComments off unless you need comments. Posts are then read from the embed page, which is about 7× smaller.
2. Leave includeProfilePosts / includeCompanyPosts off unless you need posts: they add no request but add charged results.
3. Batch your inputs. One run with 500 URLs is much cheaper than 500 runs with one URL, because every run has a start-up cost. For one-at-a-time lookups from an app, use the Standby API.
4. Memory: 512 MB is the safe default for batches of profiles and companies at 10 pages in parallel. Small runs with few parallel pages, or posts only, work in 256 MB. For very large batches, 1,024 MB can finish up to 2× faster for about the same compute units, because Apify allocates CPU in proportion to memory.
5. Leave includeJobDetails off when title, company, location and date are enough: rows take one request per 10 jobs and cost less than a third of a detailed job. Set maxJobs to what you need.
6. Standby idle time costs compute units. A warm 512 MB run uses 0.5 CU per hour while it waits. Most Standby calls handle one page (job lists at most 5 small pages at a time), so 256 MB (0.25 CU per hour) is enough for light traffic. For sporadic traffic, create a Task, open its Endpoints tab and set a short idle timeout, for example 60 s.

Is it legal to scrape LinkedIn?

This section is general information, not legal advice. Consult your own counsel.

What the Actor does and doesn't do. It reads only pages that LinkedIn serves to logged-out visitors. It uses no login data: no account, no cookies, no fake profiles, no account pools. It solves no captchas, doesn't impersonate search-engine crawlers and doesn't bypass visibility settings. When a member hides a section from the public, the Actor doesn't return it. Every result records where and when it was collected (source_url, scraped_at, input).

LinkedIn's terms. LinkedIn's User Agreement prohibits scraping, and LinkedIn actively enforces it, mostly against operators that use fake or logged-in accounts (hiQ Labs, Proxycurl, ProAPIs). US courts have found that scraping public pages while logged out is unlikely to violate the CFAA (hiQ v. LinkedIn, 9th Cir. 2019/2022), and that a platform's terms did not bar logged-off scraping of public data (Meta v. Bright Data, N.D. Cal. 2024). Guest-only collection is the lowest-risk approach, but it does not remove the contractual and commercial risk. You use the Actor at your own risk.

GDPR: you are the data controller

Profiles, employees, posts and comments contain personal data. So can job details: about half of the postings show the name, profile URL and headline of the person who posted the job. Job rows from a search or a company carry no personal data. When you run this Actor, you decide why and how that data is processed, so the GDPR obligations are yours:

• Lawful basis (Art. 6). Usually legitimate interest, supported by a documented legitimate-interest assessment. Collect only what your purpose needs: for example, leave comments, profile posts and job details off if you don't need them. Don't collect special-category data (health, religion, politics, trade-union membership) from free text.
• Inform people (Art. 14). When you collect personal data indirectly, you must tell the people concerned within a reasonable period, at the latest within one month or at your first contact with them. Tell them what you hold, the source (their public LinkedIn page, with source_url), your purpose and their rights, in their language.
• Right to object and opt-out. Keep a suppression list, and remove people who object from your inputs before future runs. Answer access requests (Art. 15) with the actual source and date. Every result carries them.
• Retention. Data in a run's default dataset is deleted automatically after your Apify plan's data-retention period. Named datasets and exports are kept until you delete them. Set your own limit, for example the French CNIL's 3-year reference for B2B prospects, and don't "refresh" old records just to extend their life.
• B2B prospecting by e-mail in France can rely on legitimate interest with a simple opt-out, provided the message relates to the person's job. This Actor doesn't collect e-mail addresses.

CNIL v. KASPR (December 2024, €240,000). The French regulator fined a tool that harvested LinkedIn contact details. The breaches were: collecting data of members who had restricted its visibility, retaining it for too long, informing people years late (and only in English), and answering access requests vaguely. This Actor is designed to avoid the first point (public data only, visibility respected) and to help with the others (provenance on every result). The remaining obligations are yours as the controller.

FAQ

Can I scrape LinkedIn without an account or cookies?

Yes. This LinkedIn scraper reads only the pages LinkedIn shows to logged-out visitors. It never logs in and never asks for credentials or cookies.

Is my LinkedIn account at risk?

No. The Actor never uses your LinkedIn account, so it can't be restricted or banned because of it.

Can I scrape LinkedIn jobs without logging in?

Yes. LinkedIn shows job postings and job search results to logged-out visitors on linkedin.com/jobs, and the Actor reads them the same way: no account, no cookies. Paste job URLs, LinkedIn jobs search URLs or company pages. See how to scrape LinkedIn jobs.

How many jobs can I get from one LinkedIn search?

Up to 1,000. LinkedIn shows at most 1,000 results per jobs search, so maxJobs goes up to 1,000 (default 25). To collect more, split the search into several URLs, for example by location or by date posted.

Why do job URLs return no posting date?

Logged out, LinkedIn's job page shows only an age such as "2 weeks ago", which you get in posted_time_ago. The date appears only in search results: job rows have posted_at (YYYY-MM-DD), and so do jobs from a search with includeJobDetails on, which keep it from their row.

Does it return the apply link of a job?

No. LinkedIn shows the external application link only to logged-in members, so linkedin_job_application_url is never filled. easy_apply tells you whether the job uses LinkedIn Easy Apply (true) or the company's own site (false), and linkedin_job_url opens the job on LinkedIn.

How do I get new LinkedIn jobs every day?

Add f_TPR=r86400 (Date posted: Past 24 hours) to a LinkedIn jobs search URL, save it in a Task and schedule the Task daily. See how to monitor new LinkedIn jobs every day.

Can I scrape all employees of a company?

No. LinkedIn lists a company's employees only to logged-in members. For each company you get the employees featured on its public page (up to 4) and li_employees_url, the LinkedIn search that lists them. If you already have employee profile URLs, add them to Profile URLs to get each full profile.

Does it find emails or phone numbers?

No. It returns what the public LinkedIn page shows, and LinkedIn doesn't show contact details to logged-out visitors.

How many LinkedIn profiles can I scrape for free?

About 1,400 profiles a month with the $5 of monthly credit included in Apify's free plan, or about 4,900 full job postings or 16,000 job search rows. See pricing.

Why are some profile fields missing?

The member hid those sections from logged-out visitors, or LinkedIn doesn't show them to guests. The Actor omits unknown fields instead of returning null.

Why did some results come back as BLOCKED?

LinkedIn refused the page on every retry from a fresh residential IP. Make sure the proxy is set to Residential, then re-run the failed inputs later. Blocked results are never charged, and raising maxRequestRetries can help on bad days.

How fast is this LinkedIn scraper?

About 0.7–1 second per page, 10 pages in parallel by default, and about half a second for a single Standby API lookup on a warm run.

Can I export LinkedIn data to Excel, CSV or Google Sheets?

Yes. Download results from the Output tab as Excel, CSV, JSON, XML or HTML, use &format=xlsx or &format=csv on the API, or send them to Google Sheets with Apify's integration.

Does it work with n8n, Make, Zapier or AI agents?

Yes. Use Apify's integrations for n8n, Make and Zapier, the Apify API clients for Python and JavaScript, or call the Standby endpoints directly over HTTP from any agent or backend.

Why is everything in one dataset?

So that one synchronous API call returns everything. Filter by entity_type.

Can I scrape LinkedIn school pages or search results?

School pages, the people directory and LinkedIn's people, company and content search are out of scope, and LinkedIn blocks them for logged-out visitors. LinkedIn jobs search results are supported: paste the search URL (see how to scrape LinkedIn jobs).

Something is broken or missing. Where do I report it?

Open an issue in the Issues tab and include the run URL and the input that failed.