Linkedin Jobs Company Scraper

LinkedIn Jobs & Company Scraper 🎯

Manually collecting job postings one by one wastes hours you don’t have. LinkedIn Jobs & Company Scraper automates scraping job listings and details at scale. This LinkedIn jobs scraper (and LinkedIn company scraper) is ideal for marketers, recruiters, and growth teams that need LinkedIn job listings scraper tool outputs fast—potentially thousands of job records in minutes from a single run.

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What You Get: Sample Output

Here’s a sample record from a single run:

{
  "title": "Senior Data Analyst",
  "location": "Dhaka, Bangladesh",
  "company_name": "ExampleTech Ltd",
  "posted_time_ago": "3 weeks ago",
  "posted_datetime": "2026-05-13T12:34:56.789012",
  "applicants": "23 applicants",
  "base_salary": "$80k–$100k per year",
  "additional_compensation": "Bonus and incentive",
  "seniority_level": "mid_senior",
  "employment_type": "full_time",
  "job_function": "data",
  "industries": "information_technology",
  "description_text": "Build and optimize analytics pipelines...\n\nResponsibilities include...",
  "description_html": "<div class=\"show-more-less-html__markup\">Build and optimize analytics pipelines...</div>",
  "job_urn": "urn:li:jobPosting:1234567890",
  "job_url": "https://www.linkedin.com/jobs/view/1234567890",
  "apply_type": "Easy Apply",
  "apply_url": "https://www.linkedin.com/jobs/view/1234567890",
  "recruiter_name": "Jane Doe",
  "recruiter_detail": "Recruiter • Talent Acquisition",
  "recruiter_image": "https://example.com/recruiter-image.jpg",
  "recruiter_profile": "https://www.linkedin.com/in/janedoe",
  "company_profile": "https://www.linkedin.com/company/exampletech/",
  "company_logo": "https://example.com/company-logo.png",
  "company_id": "99887766"
}

Field	Type	What It Tells You
title	string	The job title so you can sort and prioritize roles instantly
location	string	Where the role is based (or what location is shown on the listing)
company_name	string	The company behind the opening for lead building and segmentation
posted_time_ago	string	A quick freshness indicator like “3 weeks ago”
posted_datetime	string	A normalized ISO timestamp when available for analytics and trend tracking
applicants	string	How many applicants are shown for the posting
base_salary	string	Any base compensation text detected (often useful for qualification)
additional_compensation	string	Extra benefits/incentives if present on the posting
seniority_level	string	Seniority classification derived from job criteria items when available
employment_type	string	Employment type (for example full-time vs contract) when available
job_function	string	Job function extracted from criteria items
industries	string	Industry tags extracted from criteria items
description_text	string	Clean text you can use for keyword matching and scoring
job_url	string	Direct link to the job posting for verification and bookmarking
apply_type	string	Whether it’s shown as “External” or “Easy Apply”
recruiter_name	string	Name of the recruiter/hirer when detected on the job details
company_profile	string	Company profile link for your LinkedIn company data extraction workflow
company_id	string	Company identifier when the actor can detect it
description_html	string	HTML markup of the job description (handy if you need richer parsing)

Export your dataset as JSON, CSV, or Excel — straight from the Apify dashboard.

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Why LinkedIn Jobs & Company Scraper?

There are a lot of ways to pull data from LinkedIn job listings — here’s what sets LinkedIn Jobs & Company Scraper apart.

Bulk job detail extraction (not just shallow cards)

This LinkedIn job listings scraper tool fetches job details per posting and returns structured fields like title, company_name, description_text, and more.

Output designed for lead generation workflows

If you’re doing LinkedIn jobs and companies data mining, the dataset includes job URLs, company profile links, recruiter fields, and company identifiers—so you can build actionable lists faster.

Built-in resilience for real-world scraping

It includes retry handling for blocked or unstable requests and keeps the run moving so you get results even when some pages don’t respond cleanly.

Clean, structured JSON ready to analyze

Each result is pushed as a consistent JSON object with predictable keys (for example job_urn, job_url, apply_type, apply_url, recruiter_*, company_*), making it easy to load into spreadsheets, BI tools, or CRMs.

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Configuring Your Run

Drop this into your input.json to get started:

{
  "search_url": "https://www.linkedin.com/jobs/jobs-in-bangladesh",
  "max_results": 50
}

Parameter	Required	What It Does
search_url	✅	The LinkedIn jobs search URL you want to scrape from (supports different job search URLs)
max_results	✅	Maximum number of jobs to scrape from the search results

Note: The actor code also supports proxy configuration via an input field named proxyConfiguration, but it’s not included in the provided actor input schema. If you see proxyConfiguration in your Apify UI, you can use it to enable built-in proxy support for more reliable scraping.

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Core Capabilities

Scrapes job postings into structured fields

LinkedIn Jobs & Company Scraper is built to extract job-specific details such as title, location, posted_datetime, description_text, and compensation when available—ideal for people building datasets from public web data.

Company and recruiter context included

For LinkedIn company contact scraper and recruiter-related workflows, each record includes company_name, company_profile, recruiter fields like recruiter_name, plus recruiter_profile and recruiter_image when detected.

Uses your search URL + result cap for predictable runs

You control the source via search_url and set an explicit cap with max_results, which makes LinkedIn jobs scraper with filters workflows easier to operationalize (even when you only have the search URL available).

Resilient fetching with retries and fallbacks

When requests are blocked or unstable, the actor handles those cases and retries appropriately, helping avoid “all-or-nothing” failures during longer LinkedIn automation for job scraping runs.

Real-time dataset writing (so you keep progress)

Each successfully fetched job detail record is pushed immediately to the dataset, so you can export partial results if you stop a run early.

In short: you get a dataset that’s ready for LinkedIn jobs lead generation, analysis, and outreach building—without manually clicking each job.

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Who Gets the Most Out of This

Here’s how different teams put LinkedIn Jobs & Company Scraper to work:

Recruiters & Talent Sourcers — Build a shortlist of roles and companies by exporting job titles, locations, and recruiter fields into a spreadsheet, then quickly filter for seniority and employment type.

Sales Development Representatives — Use the extracted company_profile and job_url to create targeted prospect lists and reduce prospecting time when your ICP hires through job postings.

Market Researchers & Data Analysts — Turn job description content into structured datasets using description_text plus timestamp fields like posted_datetime to study hiring trends over time.

Automation & Integration Developers — Pull consistent JSON outputs via the Apify platform, then map fields like apply_type, base_salary, and recruiter_profile into your pipeline without custom parsing.

Growth Teams & HR Operations — Monitor recurring job openings and keep a “current roles” dataset for internal reporting, competitor benchmarking, and workflow automation using exports from the dataset tab.

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Step-by-Step: How to Use It

No coding needed. Here's how to run LinkedIn Jobs & Company Scraper from start to finish:

1. Open the actor on Apify — Go to console.apify.com and open LinkedIn Jobs & Company Scraper.
2. Enter your inputs — Set search_url to your LinkedIn jobs search URL and choose max_results for how many jobs you want to scrape.
3. Configure proxy support (optional) — If you need more reliable scraping at higher volume, enable proxy settings available in the Apify interface.
4. Hit Run and watch the live log — Monitor progress as job postings are processed and details are fetched.
5. View results in the dataset tab — Open the dataset to inspect the JSON records as they’re produced.
6. Export as JSON, CSV, or Excel — Use the export options from the Apify dataset UI for downstream use.

The whole process takes under 5 minutes to set up.

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Integrations & Export Options

Once your data is collected, LinkedIn Jobs & Company Scraper plugs directly into your existing workflow.

Export your results from the Apify dataset tab as JSON, CSV, or Excel. That makes it straightforward to enrich spreadsheets, dashboards, and lead lists with fields like job_url, company_profile, and description_text.

You can also connect the actor to automation systems using Apify’s capabilities (for example, via the Apify API), and you can use webhook-based patterns supported by Apify workflows to trigger downstream steps (CRM updates, notifications, and more). For the most up-to-date details, refer to the Apify documentation linked from the Apify developer resources: https://apify.com/docs/api

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Pricing & Free Trial

LinkedIn Jobs & Company Scraper runs on the Apify platform, which offers a free tier — no credit card required to get started. Free tier credits (and paid usage) are handled by Apify’s platform billing model, typically based on Apify compute usage (CU), not per-row fees from your dataset.

For exact current pricing, credits, and plan limits, check the Apify pricing page. Start for free at apify.com and scale when you're ready.

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Reliability & Performance

What We Handle	How
Rate limiting and unstable responses	Includes retries and backoff behavior for blocked/failed requests
Proxy-assisted reliability	Supports built-in proxy usage if enabled in your run
Partial progress capture	Successfully fetched jobs are pushed to the dataset as they’re processed
Missing fields on some postings	Returned values may be null or omitted depending on what the page provides
Scaling to your cap	The run respects your max_results limit for predictable output volume

Limitations: This actor works with publicly accessible job details available through the provided search URL. If some postings don’t provide certain data points (like salary or recruiter details), those fields may be missing or empty in the output. For enterprise-scale configurations, contact us to discuss your needs.

For enterprise-scale runs, contact us to discuss custom configurations.

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Frequently Asked Questions

Is there a free plan or trial?

Yes. Apify provides a free tier so you can run LinkedIn Jobs & Company Scraper for testing before scaling up.

Do I need to log in to LinkedIn to use this?

No login is required for the inputs you provide (the actor is designed to scrape job details from publicly available data).

How accurate is the data?

The accuracy depends on what’s available on the job postings and job details pages. The actor extracts structured fields like title, company_name, and description_text when they exist in the source content.

How many results can I get per run?

You control the maximum number of scraped jobs using max_results. The actor stops when it reaches that cap.

How often is the data updated / how fresh is it?

Freshness depends on how current the underlying job postings are at the time you run. The dataset includes posted_time_ago and a normalized posted_datetime field when it can determine the posting time.

Is this legal? Does it comply with GDPR / CCPA?

You should use this tool only for lawful purposes and in compliance with applicable regulations (including GDPR and CCPA) and platform rules. The actor collects publicly available data, but responsibility for compliant use remains with you.

Can I export results to Google Sheets or Excel?

Yes. You can export your dataset from the Apify dashboard, and Excel-friendly formats like CSV and JSON exports make it easy to move data into spreadsheets. You can also connect your results to other tools using Apify-supported automation patterns.

Can I run this on a schedule automatically?

Yes. You can schedule actor runs on the Apify platform using supported scheduling capabilities, so your job listings dataset stays updated without manual effort.

Can I access this via API?

Yes. Apify actors can be triggered and monitored via the Apify API, and you can fetch results programmatically from the produced dataset. See Apify API docs for details: https://apify.com/docs/api

What happens if the actor hits an error?

If some requests fail, the actor uses retry handling for blocked or unstable responses and continues processing where possible. If a fetch fails for a job detail, that job may return no result, but the run can still produce other records you can export.

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Need Help or Have a Request?

Got a question about LinkedIn Jobs & Company Scraper or want a new feature added? Reach out at dataforleads@gmail.com — we actively maintain this actor and welcome feedback. If you’d like enhancements like webhook notifications on completion or additional filtering options, tell us what you need.

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Disclaimer & Responsible Use

LinkedIn Jobs & Company Scraper is the fastest, most reliable way to build structured datasets from public job postings — start your free run today.

This actor collects publicly available data only and does not access private accounts, login-gated content, or password-protected pages. You are responsible for complying with GDPR, CCPA, platform ToS, and any applicable laws. For data removal requests, contact dataforleads@gmail.com. Use responsibly, ethically, and only for lawful purposes.