LinkedIn Jobs Scraper + Glassdoor: one dataset, with salaries and skills

Scrape LinkedIn jobs and Glassdoor jobs in a single run and get back one clean, deduplicated dataset: same field names and shapes, whichever site a job came from. Every listing has title, company, location, posted date and job link. Glassdoor listings add salary (~76%), skills and company rating. With full details on, LinkedIn jobs get skills (~99%) and pay (about half of US postings) read from the job description. Export as JSON, CSV or Excel, or pull it through the API.

No login, no cookies, no browser. It sends plain HTTP requests, which is why it is fast and costs a fraction of what browser-based job scrapers charge. From $0.40 per 1,000 jobs.

~850 LinkedIn jobs in 87 seconds. 500 Glassdoor jobs in 10 seconds.

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Why this one

Most job scrapers on the Store do a single site. Running two of them gets you two different schemas, two sets of duplicates and two bills.

	This Actor
Sites per run	LinkedIn + Glassdoor
Output schema	one unified schema
Duplicates across sites	removed
Salary	Glassdoor: ~76% of listings. LinkedIn with fetchDetails: ~50% in the US, ~10% in India, read from the description
Skills	Glassdoor: 100% of listings. LinkedIn with fetchDetails: ~99%, read from the description
Company ratings	Glassdoor
"Only new jobs" mode for schedules	yes
Price per 1,000 jobs	from $0.40, no start fee

The two sites complement each other: LinkedIn brings volume and full job descriptions, Glassdoor brings salary, skills and employer ratings. LinkedIn's public pages have no skills field and rarely a salary field, so with fetchDetails on the Actor reads both from the job description.

Who uses it

• Recruiters and staffing agencies: find every company hiring for a role in a city, with salary ranges to pitch against.
• Job boards and job-alert apps: a daily feed of fresh postings from two sources in one schema, with onlyNewJobs so you never pay twice for the same job.
• Salary and labour-market research: Glassdoor pay ranges and skills by title, location and company.
• Sales and lead generation: companies that are hiring are companies with budget.
• AI agents and LLM apps: structured job data through the Apify API or the Apify MCP server.

How to scrape LinkedIn and Glassdoor jobs

1. Enter one or more keywords (e.g. data analyst) and locations (e.g. India, London, Remote), or paste a LinkedIn or Glassdoor search URL.
2. Pick the sources, how many jobs you want, and how recent (24h, week, month).
3. Click Start. Download the results as JSON, CSV or Excel, or fetch them through the API.

What you get for every job

Every field is always present — unknown values are null, never missing — so CSV and Excel exports keep stable columns.

Group	Fields
Identity	id, source, sourceJobId, url, applyUrl
Role	title, description, descriptionHtml, jobFunction, industry
Company	company, companyUrl, companyLogo, companyRating, and with fetchDetails: companySize, companyEmployees, companyIndustry, companyWebsite, companyDescription, companyFounded, companyAddress
Place & type	location, workType (remote / hybrid / on-site), jobType
Pay	salary.min, .max, .currency, .period, .raw, .source
Experience	experienceLevel, experienceYears.min, experienceYears.max
Skills	skills[]
Timing & signals	postedAt, postedAtRaw, applicants, easyApply, activelyHiring, earlyApplicant
Provenance	searchKeyword, searchLocation, detailsFetched, scrapedAt

salary.source says where a figure came from: EMPLOYER_PROVIDED or ESTIMATED (Glassdoor), or description when it was read from the job text, so you can filter down to the pay you trust.

Example output

{
  "id": "glassdoor:1010260754808",
  "source": "glassdoor",
  "title": "Mid-Level Developer – AI-Enabled Systems (Remote, India)",
  "company": "Best Access Doors",
  "companyUrl": "https://www.glassdoor.com/Overview/-EI_IE3727326.htm",
  "companyRating": 4.6,
  "location": "Bengaluru",
  "workType": "remote",
  "salary": {
    "min": 360000,
    "max": 760000,
    "currency": "INR",
    "period": "year",
    "raw": "INR 360,000 - INR 760,000 per year",
    "source": "ESTIMATED"
  },
  "skills": ["Authentication", "Technical troubleshooting", "Systems integration"],
  "postedAt": "2026-09-12T18:44:42.083Z",
  "postedAtRaw": "29d",
  "easyApply": false,
  "jobFunction": "it engineer",
  "searchKeyword": "react developer",
  "searchLocation": "India"
}

Pricing

Pay per result. You are charged for jobs you actually receive, nothing else.

Event	What it is	Free plan	Bronze	Silver	Gold and up
job	title, company, location, salary when shown, skills, rating, posted date, link	$0.40	$0.36	$0.32	$0.30
job-with-details	all of the above plus the full description, applicant count, seniority and industry	$1.20	$1.08	$0.96	$0.90

Prices are per 1,000 jobs. No start fee, no monthly rent.

Set a max cost per run in the run options and the Actor stops the moment it is reached, so it never overshoots your budget.

Two ways to search

1. Keywords and locations. Every keyword is searched in every location.

{
  "keywords": ["react developer", "python developer"],
  "locations": ["India", "Bangalore"],
  "sources": ["linkedin", "glassdoor"],
  "maxItemsPerSource": 500,
  "postedWithin": "week",
  "fetchDetails": false
}

2. Paste a search URL. Build the search on LinkedIn or Glassdoor with whatever filters you like and paste the URL. Each URL runs only against the site it came from.

{
  "startUrls": [
    "https://www.linkedin.com/jobs/search?keywords=react%20developer&location=India",
    "https://www.glassdoor.com/Job/bengaluru-react-developer-jobs-SRCH_IL.0,9_IC2940587_KO10,25.htm"
  ]
}

Options worth knowing

• fetchDetails — everything about the job and the employer: full description, applicants, seniority, skills and salary, plus company size, employee count, address, website and description. Priced as a detailed job. Off by default: basic is cheaper and faster.
• onlyEarlyApplicants — LinkedIn jobs marked "Be an early applicant", so you apply before the crowd. LinkedIn applies it itself. (LinkedIn's public pages show "first 25 applicants" at best, so no scraper can honestly promise an exact "under 10".)
• onlyNewJobs — remembers every job id already returned to you and skips it next time. Ideal with a daily schedule: you only pay for jobs you have not seen.
• dedupeAcrossSources — when the same role is posted on both sites, return it once.
• postedWithin — 24h, week, month or any.
• minCompanyRating, companySize, searchRadius — Glassdoor's own filters: employer rating (1.0+ to 4.0+), company size (1-200 up to 5,001+ employees) and miles around a city. Glassdoor applies them before results come back, so they cost nothing extra. LinkedIn has no equivalent.
• maxItemsPerSource — hard stop per site.

Speed, and the limits worth knowing

Better said up front than discovered later.

• LinkedIn returns ~854–868 unique jobs per keyword + location, because its public search caps a query at roughly 1,000 results. Use more keywords or locations to go wider.
• Glassdoor reports how many jobs a search has (often thousands) and this Actor pages through them 100 at a time.
• LinkedIn ignores the work type, job type and experience level filters on its public search. Glassdoor applies all three. The run warns you rather than pretending otherwise. postedWithin works on both.
• LinkedIn pay and skills need fetchDetails: they are read from the job description, which only the detail page has. US postings state pay about half the time (pay-transparency laws), Indian ones far less. Glassdoor supplies both either way.
• Fields a site does not expose come back null. Nothing is guessed: a LinkedIn salary is only taken from a line that states pay, never from bonuses, benefits or funding figures.

Integrations

The output is an ordinary Apify dataset, so anything Apify supports works:

• API — GET https://api.apify.com/v2/datasets/<datasetId>/items?format=json (also csv, xlsx, xml, rss)
• Make, Zapier, n8n — through the Apify connectors
• Scheduled runs — a daily schedule plus onlyNewJobs: true gives you a feed of new postings
• Webhooks — fire on run completion to push results into your own system

Ready-made n8n workflow: new jobs in Google Sheets every morning

Import it and get a daily sheet of new LinkedIn and Glassdoor jobs, with no repeats: title, company, location, salary, skills, rating and link. Built-in n8n nodes only, set up in about 3 minutes. Workflow and setup steps: n8n community post.

FAQ

Do I need a LinkedIn or Glassdoor account or cookies?

No. Only public job listings are read. You are never asked for a login, credentials or cookies, so no account of yours is at risk.

How much does it cost to scrape 1,000 LinkedIn jobs?

$0.40 for 1,000 jobs, or $1.20 with full descriptions (fetchDetails). There is no start fee and no monthly rent. Set a max cost per run and the Actor stops the moment it is reached.

Is it legal to scrape LinkedIn and Glassdoor jobs?

The Actor reads publicly available job postings only. It collects no personal data and no candidate profiles. How you use the data is your responsibility, so check the rules that apply to your use case.

How do I get only new jobs every day?

Create a daily schedule and set onlyNewJobs: true. The Actor remembers every job it has returned to you and skips it next time, so you only pay for postings you have not seen.

Can I get salary data?

Yes. Glassdoor supplies a salary range for about 76% of listings, and salary.source says whether the employer published it or Glassdoor estimated it. For LinkedIn, turn on fetchDetails: pay is read from the description (about half of US postings, ~10% in India) and marked salary.source: "description".

Can I export to Excel, CSV or Google Sheets?

Yes. Every run's dataset downloads as JSON, CSV, Excel, XML or RSS, and the Make, Zapier and n8n integrations push it to Google Sheets, Airtable or your CRM.

What if one site is temporarily unavailable?

The other still finishes, and the run reports which source could not be reached. You are not charged for jobs you did not get.

Why is a field empty?

Because the site did not publish it for that listing. Nothing is inferred, so an empty field is information too.

Can you add Indeed, Naukri or another job board?

Tell us on the Issues tab which board you need. Requests decide what gets added next.