Glassdoor Job Scraper | 22 Countries, Salary & Company Ratings

What does Glassdoor Job Scraper do?

Glassdoor Job Scraper extracts structured job listings from Glassdoor across 22 country sites — including the US, UK, Canada, Australia, India, Germany, France, Spain, Brazil, Mexico and 12 more. Each record delivers salary ranges, extracted skills, full descriptions in three formats, and deep company intelligence with 9 individual rating dimensions (CEO approval, culture, compensation, career opportunities, work-life balance, senior management and recommend-to-friend). No code needed — results export as JSON, CSV, Excel, or via the API, ready for spreadsheets, dashboards, AI agents and MCP workflows.

Give it a search keyword (e.g. software engineer) and pick a country, or paste Glassdoor URLs directly. The scraper returns every matching listing as a clean, typed record. Core fields (title, employer, salary, location, skills) come from the listing itself; turn on Fetch full details to also pull the complete job description and company overview — ratings, size, sector, headquarters, revenue, founding year and website.

New to Apify? You can sign up for free and use the included monthly platform credit to try this Actor.

Why this scraper

• ⚡ Fast & low-cost — direct HTTP extraction with no browser overhead, so large runs stay cheap.
• 🧾 Rich, typed records — 65+ structured fields per job, not raw HTML.
• ♻️ Cheap to monitor — incremental mode re-scrapes only what changed (see below).
• 🔔 Notifications built in — Telegram, Slack, Discord, WhatsApp or any webhook.
• 🤖 AI- & API-ready — compact output, MCP-friendly, one-click integrations.

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Key features

• 🌍 22-country coverage — search Glassdoor in the US, UK, Canada, Australia, India, Germany, France, Spain, Brazil, Mexico, Argentina, Netherlands, Belgium, Switzerland, Austria, Ireland, New Zealand, Singapore, Hong Kong and Italy — from a single dropdown.
• 📍 Location search — type a city or region (e.g. "New York, NY") and the scraper resolves it automatically via Glassdoor's location API, with optional radius filtering.
• 🔎 Search or URL scraping — run a keyword + filter search, or paste Glassdoor search and job listing URLs.
• 💰 Salary intelligence — min, median and max salary with currency, period and source metadata.
• 🏢 Deep company intelligence — 9 rating dimensions (CEO approval, culture, compensation, career opportunities, work-life balance, senior management, recommend-to-friend), CEO name, review count, size, industry, sector, headquarters, revenue, type, year founded and website.
• 🛠️ Extracted skills — the full skills and attributes list that Glassdoor tags on each listing.
• 📍 Parsed locations — city, region and country split out alongside the raw location string, plus a remote flag and apply URL per listing.
• 🎚️ Rich filters — date posted, job type, work setting (remote/hybrid/on-site), seniority level, Easy Apply, salary range, employer size, minimum company rating, and job-ID exclusion — all applied by Glassdoor itself.
• ♻️ Incremental monitoring — schedule it and get only what changed (NEW / UPDATED / EXPIRED); unchanged items are skipped before their page is even fetched. firstSeenAt / lastSeenAt timestamps track each listing across runs.
• 🔔 Notifications — Telegram, Slack, Discord, WhatsApp Cloud API or any webhook (n8n / Make / Zapier). Optionally notify only on changes.
• 🤖 AI-ready — compact + drop-empty output modes keep payloads small for LLMs and MCP.

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🚀 How to scrape Glassdoor

1. Open the actor and enter a search keyword (e.g. data scientist) and pick a country — or paste a Glassdoor URL.
2. Set Max results and choose whether to fetch full details (on by default).
3. Apply filters — date posted, job type, work setting, seniority, salary range, employer size.
4. (Optional) Turn on incremental mode and a notification channel, then Schedule it.
5. Click Start.
6. Download the data as JSON, CSV or Excel, or pull it from the API.

New to Apify? Create a free account — it comes with monthly credit, no credit card required.

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Input

Configure it in the visual editor — no code needed — or pass JSON via the API.

Field	What it does
query	Keyword search (comma-separate for multiple searches).
country	Which Glassdoor country site to search (22 countries).
location	City or region to search in — resolved via Glassdoor's location API.
startUrls	Scrape specific Glassdoor search or job listing URLs.
datePosted	Only show jobs posted within a time range (24 h to 30 days).
jobType	Filter by Full-time, Part-time, Contract, Internship or Temporary.
remoteWorkType	Remote, Hybrid or On-site.
seniorityType	Entry Level, Mid-Senior Level, Director or Executive.
minSalary / maxSalary	Salary range filter (local currency).
radius	Distance in miles from the search location.
minRating	Only show jobs from companies rated at least this high (1.0–5.0).
employerSize	Filter by company size (1-200 up to 5,001+).
easyApply	Show only Easy Apply jobs.
includeDetails	Fetch full description and company intelligence per job.
includeCompanyProfile	Toggle company ratings, CEO, size, revenue and other company fields.
requireContact	Keep only listings with an email, phone or both — built-in lead-gen filter.
compact	Return only core fields — ideal for AI agents and MCP clients.
incrementalMode	Emit only what changed since the last run.
skipReposts	Skip jobs detected as reposts of previously seen listings.
maxResults	Cap the number of records (0 = unlimited).
excludeJobIds	List of job IDs to exclude from results.

...and 42 inputs in total — the table shows the essentials; the rest cover notification channels (Telegram, Slack, Discord, WhatsApp, webhook), description format, output/AI modes and advanced tuning, all in the visual editor.

Example inputs

Basic search — 100 software engineer jobs in the US:

{ "query": "software engineer", "country": "United States", "maxResults": 100 }

Filtered search — remote data science roles, last 7 days, Easy Apply only:

{
  "query": "data scientist",
  "country": "United States",
  "datePosted": "7",
  "remoteWorkType": ["remote"],
  "easyApply": true,
  "maxResults": 50
}

Incremental monitoring — daily watch for new marketing jobs in Germany with Slack alerts:

{
  "query": "marketing manager",
  "country": "Germany",
  "incrementalMode": true,
  "slackWebhookUrl": "https://hooks.slack.com/services/..."
}

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Output

Each item in the dataset is one job listing. Every record includes the core fields; enabling Fetch full details (on by default) adds the full description, company ratings and company overview. Here is a real example record:

{
  "id": "1010207918748",
  "title": "Software Engineer (Remote Opportunity)",
  "url": "https://www.glassdoor.com/job-listing/software-engineer-remote-opportunity-...",
  "applyUrl": "https://www.glassdoor.com/partner/jobListing.htm?...",
  "source": "glassdoor.com",
  "searchKeyword": "software engineer",
  "scrapedAt": "2026-08-24T07:13:01.391613+00:00",
  "detailFetched": true,

  "employerName": "Universal Background Screening",
  "employerId": "737244",
  "employerRating": 2.5,

  "locationName": "Phoenix, AZ",
  "locationCity": "Phoenix",
  "locationRegion": "AZ",
  "locationCountry": "United States",
  "isRemote": false,
  "sourceCountry": "us",
  "sourceDomain": "www.glassdoor.com",

  "salaryMin": 63186,
  "salaryMedian": 80369,
  "salaryMax": 102225,
  "salaryCurrency": "USD",
  "salaryPeriod": "ANNUAL",
  "salarySource": "ESTIMATED",

  "ageInDays": 31,
  "easyApply": true,
  "isExpired": false,
  "normalizedJobTitle": "software engineer",
  "jobCategory": "software engineer",
  "skills": ["Jira", "Azure", "SQL", ".NET Core", "AWS Lambda", "MongoDB", "..."],

  "description": "The Software Engineer is responsible for designing, developing, and maintaining ...",
  "descriptionHtml": "<div><p>The Software Engineer is responsible for ...</p>...</div>",
  "descriptionMarkdown": "**Job Summary:** The Software Engineer is responsible for ...",
  "descriptionLength": 4772,

  "companyRating": 2.5,
  "companyCeoRating": 0.19,
  "companyCeoRatingsCount": 28,
  "companyWorkLifeBalanceRating": 2.5,
  "companyCultureRating": 2.3,
  "companyCompensationRating": 1.9,
  "companyCareerOpportunitiesRating": 1.9,
  "companySeniorManagementRating": 2.2,
  "companyRecommendToFriendRating": 0.28,
  "companyReviewsCount": 13373,

  "companySize": "201 to 500 Employees",
  "companySector": "Management & Consulting",
  "companyWebsite": "https://www.universalbackground.com",
  "companyHeadquarters": "Phoenix, AZ",
  "companyRevenue": "$25 to $100 million (USD)",
  "companyType": "Company - Private",
  "companyYearFounded": 2002,
  "companyCeo": "Jane Smith"
}

Each record can also include descriptionHtml and descriptionMarkdown — choose the format with the Description format input. When incremental mode is on, records carry a changeType field (NEW / UPDATED / EXPIRED) and repost-detection fields.

Data fields

• Core — id, title, url, applyUrl, source, searchKeyword, scrapedAt, detailFetched.
• Employer — employerName, employerId, employerRating, companyLogo.
• Location — locationName, locationCity, locationRegion, locationCountry, locationType, isRemote, sourceCountry, sourceDomain.
• Salary — salaryMin, salaryMedian, salaryMax, salaryCurrency, salaryPeriod, salarySource.
• Job details — description (text / HTML / Markdown), descriptionLength, employmentType, ageInDays, easyApply, isExpired, isSponsoredJob, normalizedJobTitle, jobCategory, skills.
• Company ratings (9 dimensions) — companyRating, companyCeoRating, companyCeoRatingsCount, companyWorkLifeBalanceRating, companyCultureRating, companyCompensationRating, companyCareerOpportunitiesRating, companySeniorManagementRating, companyRecommendToFriendRating, companyReviewsCount.
• Company overview — companyCeo, companySize, companyIndustry, companySector, companyWebsite, companyHeadquarters, companyRevenue, companyType, companyYearFounded.
• Contacts & signals — extractedEmails, extractedPhones, extractedUrls, socialProfiles.
• Incremental / repost — changeType, contentHash, firstSeenAt, lastSeenAt, isRepost, repostOfId, repostDetectedAt.

Every field is present in standard mode (missing values are null); compact mode returns the core fields only, for lean AI/MCP payloads. With excludeEmptyFields enabled, null/empty fields are omitted entirely.

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💡 What can you do with Glassdoor data?

• Salary benchmarking — compare salary ranges by role, seniority, location and company size across 22 markets.
• Employer intelligence — rank companies by their 9 rating dimensions to identify the best (or worst) employers in an industry.
• Lead generation — filter for listings with contact details using requireContact and feed them into your CRM or outreach tool.
• Job market monitoring — schedule incremental runs with notifications to track new openings, expired listings and salary changes daily.
• Enrichment & aggregation — feed clean, structured job data into your own app, spreadsheet or data warehouse.
• AI agents & pipelines — compact output plugs straight into LLM/MCP workflows for talent analytics, resume matching or market research agents.

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♻️ Incremental monitoring — pay for changes, not repeats

Schedule the actor and turn on incremental mode: each run compares against the last and emits only NEW / UPDATED / EXPIRED records — unchanged items are skipped before their detail page is fetched, so a daily watch costs a fraction of a full re-scrape.

Daily churn	of 1,000 tracked	billable records	you save
5 %	1,000	50	95 %
15 %	1,000	150	85 %
30 %	1,000	300	70 %

The first run seeds the baseline and bills in full; every run after that bills only the delta. Repost detection also flags relisted jobs so you never count them as genuinely new.

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💰 How much does it cost to scrape Glassdoor?

This Actor uses the pay-per-event pricing model: a small fee at run start plus a per-record fee. It runs on direct HTTP with no browser overhead, so the underlying platform cost is minimal.

See the Actor's Pricing tab for exact current prices.

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🔌 Integrations & export

Export to JSON, CSV, Excel or an HTML table, or pull from the REST API and the JavaScript / Python clients. Runs on a schedule, connects to Google Sheets, Slack, Make, Zapier and n8n, and works as an MCP tool for AI agents — compact mode keeps token usage small.

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🔗 Using the API

You can run this Actor from your own code. Example with the Apify Python client:

from apify_client import ApifyClient

client = ApifyClient("<YOUR_API_TOKEN>")

run_input = {
    "query": "software engineer",
    "country": "United States",
    "maxResults": 50,
}

run = client.actor("corvuslab/glassdoor-scraper").call(run_input=run_input)

print("Results: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

The Actor also works with the JavaScript/TypeScript client, the Apify CLI and the REST API.

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❓ FAQ

Do I need a proxy or login? No — it runs out of the box with no login and no proxy required. Apify Proxy is available under Advanced for high-volume runs.

Can I search multiple countries? One country per run, but you can schedule separate runs or use comma-separated keywords to cover multiple searches within a country.

Can I search by city or region? Yes — type a city name (e.g. "San Francisco, CA") in the location field. The scraper resolves it via Glassdoor's location API and you can set a radius in miles for nearby results.

Can I get only new jobs on a schedule? Yes — turn on incremental mode and schedule it; each run emits only what changed and can notify your channel via Telegram, Slack, Discord, WhatsApp or a webhook.

What formats can I export? JSON, CSV, Excel, HTML table, or via the API.

Is it good for AI agents? Yes — enable compact mode; the output is MCP-friendly and keeps token usage small.

How many records can I get? Set maxResults to any number (0 = unlimited). Results are bounded only by what the search returns.

What are the 9 company rating dimensions? Overall rating, CEO approval, work-life balance, culture & values, compensation & benefits, career opportunities, senior management and recommend-to-friend — each as a separate numeric field.

Is scraping Glassdoor legal? This actor collects only publicly available data on Glassdoor. You are responsible for how you use the extracted data — in particular any personal information — and for complying with the site's terms and applicable law (including the GDPR where it applies). Not affiliated with, endorsed by, or sponsored by Glassdoor, Inc.

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