LinkedIn Job Scraper (by Job URL)

What does LinkedIn Job Scraper (by Job URL) do?

LinkedIn Job Scraper (by Job URL) extracts detailed job information from LinkedIn by job detail page URL. Provide one or more LinkedIn job URLs, and it will fetch each page and return structured job data including title, company, salary, description, and applicant count.

• Accept one or more LinkedIn job detail page URLs
• Extract structured job data from each page
• Get salary information including structured base salary
• Retrieve job poster details
• Get formatted job descriptions in HTML
• Control concurrency for parallel fetching
• Built-in retry logic for reliable data collection

What data can you get from LinkedIn

LinkedIn Job Scraper (by Job URL) extracts comprehensive job data, such as:

How to scrape LinkedIn with LinkedIn Job Scraper (by Job URL)?

LinkedIn Job Scraper (by Job URL) is straightforward to use. Follow these 5 steps:

1. Prepare one or more LinkedIn job detail page URLs (e.g. https://www.linkedin.com/jobs/view/1234567890/).
2. Add the URLs to the input list.
3. Optionally adjust concurrency and retry settings.
4. Click the "Start" button and wait for the data to be extracted.
5. Download your data in JSON, CSV, Excel, or other available formats.

Input

LinkedIn Job Scraper (by Job URL) accepts the following input parameters:

• url (required): Array of LinkedIn job detail page URLs
• retry_times: Request retry count (1–5). Default: 3
• max_concurrency: Concurrent requests (1–20). Default: 8

Input JSON

{
    "url": [
        {"url": "https://www.linkedin.com/jobs/view/1234567890/"},
        {"url": "https://www.linkedin.com/jobs/view/9876543210/"}
    ],
    "retry_times": 3,
    "max_concurrency": 8
}

Output

Each input URL returns one row with structured job data:

{
    "url": "https://www.linkedin.com/jobs/view/1234567890/",
    "status": "success",
    "data": {
        "url": "https://www.linkedin.com/jobs/view/1234567890/",
        "job_posting_id": "1234567890",
        "job_title": "Senior Python Developer",
        "company_name": "Example Corp",
        "company_id": "12345",
        "job_location": "San Francisco, CA",
        "job_summary": "We are looking for a senior Python developer...",
        "job_seniority_level": "Mid-Senior level",
        "job_function": "Engineering",
        "job_employment_type": "Full-time",
        "job_industries": "Technology",
        "job_base_pay_range": "$120,000/yr - $180,000/yr",
        "base_salary": {
            "currency": "USD",
            "min_amount": 120000,
            "max_amount": 180000,
            "payment_period": "YEARLY"
        },
        "salary_standards": "",
        "company_url": "https://www.linkedin.com/company/example-corp/",
        "job_posted_time": "3 days ago",
        "job_posted_date": "2025-09-01T00:00:00.000Z",
        "job_num_applicants": 42,
        "application_availability": true,
        "apply_link": "",
        "country_code": "US",
        "title_id": "",
        "company_logo": "https://media.licdn.com/...",
        "job_poster": {
            "name": "Jane Smith",
            "title": "Engineering Manager",
            "url": "https://www.linkedin.com/in/janesmith/"
        },
        "job_description_formatted": "<h3>About the role</h3><p>...</p>"
    },
    "error": "",
    "error_code": ""
}

How can I use the data?

• 📋 Track specific jobs — Monitor saved job postings for updates on applicant count or application status
• 💼 Bulk data collection — Extract details for a curated list of jobs in one run
• 📊 Salary benchmarking — Compare compensation across specific roles you're interested in
• 🔍 Job comparison — Analyze requirements, benefits, and descriptions across multiple positions
• 📈 Application tracking — Build a personal database of jobs you've applied to or are considering
• 🤖 Data pipeline integration — Feed structured job data into your existing workflows or databases

Error items

When the scraper cannot retrieve data for a given URL, it pushes an error item to the dataset. Normal output items are never affected; you can tell them apart by the presence of an error_code field.

Error item structure

{
    "url": "https://www.linkedin.com/jobs/view/1234567890/",
    "status": "failed",
    "data": null,
    "error": "Job posting not found",
    "error_code": "NOT_FOUND"
}

Error codes reference

FAQ

How is this different from LinkedIn Job Scraper (by Keyword)?

This scraper works with specific job URLs you already have. If you want to search for jobs by keyword and location, use LinkedIn Job Scraper (by Keyword) instead.

Can I mix different types of URLs in the same input?

No. This scraper is designed specifically for LinkedIn job detail page URLs (e.g. https://www.linkedin.com/jobs/view/...). For listing page URLs, use LinkedIn Job Scraper (by Listing URL).

How many URLs can I submit at once?

There is no hard limit on the number of URLs. However, the max_concurrency setting controls how many pages are fetched in parallel, so more URLs will take proportionally longer.

What happens if a job posting has been removed?

The scraper will return an error item with error_code: "NOT_FOUND" for that URL while continuing to process the remaining URLs.

Is it legal to scrape LinkedIn job data?

This scraper only extracts publicly available job listing data. You should ensure your use of the data complies with LinkedIn's terms of service and applicable laws in your jurisdiction.