Glassdoor Scraper — Reviews, Salaries, Interviews & Jobs

Disclaimer: Unofficial tool for publicly accessible Glassdoor employer and job pages. Glassdoor and related names are trademarks of their respective owners. Not affiliated with, sponsored by, or endorsed by Glassdoor / Indeed / Recruit Holdings. For informational, research, and recruiting-intelligence use only. Respect applicable terms of use and law.

Scrape Glassdoor employer intelligence as structured JSON: company ratings, employee reviews (pros/cons, titles, dates), interview questions, salary bands, and job listings with pay ranges. Resolve plain company names, paste Overview / Reviews / Jobs URLs, or pass employer IDs. Run keyword × location job search across 15+ country domains. A practical Glassdoor API alternative — call from Python, Node.js, cURL, or Apify MCP.

Ideal for HR due diligence, employer-brand monitoring, compensation research, interview prep, and recruiting pipelines.

Crawloop Jobs Suite — global Glassdoor employer intel + DACH board coverage.

Glassdoor (global employer intel)	Arbeitsagentur (DE public jobs)	Stepstone (DACH commercial board)
Glassdoor Scraper ◄── you are here	Arbeitsagentur Jobs Scraper	Stepstone Jobs Scraper

When to use this Actor

• You need a Glassdoor scraper for reviews, interviews, salaries, or jobs as JSON
• You want company name resolve instead of hunting employer URLs by hand
• You chain DACH job boards → Glassdoor for global reputation on the same employers
• You want a Glassdoor API alternative from Python, Node.js, or an MCP / AI assistant

When not to use this Actor

• Germany public Jobbörse only — use Arbeitsagentur Jobs Scraper
• DACH commercial board search — use Stepstone Jobs Scraper
• Login-walled / give-to-get full review text — public pages and JSON only; this Actor does not log in
• Guaranteed thousands of reviews per employer — public HTML/JSON-LD often ships a rated sample; extra pages are collected while they return data

Key Features

• Company-centric + job search — names, URLs, employer IDs, or keyword × city
• Typed dataset rows — company, review, interview, salary, job
• Ratings & review snippets from public Overview / Reviews pages (JSON-LD + cards)
• Jobs with pay ranges — listing cards include title, location, salary band, URL
• 15+ domains — .com, .co.uk, .de, .fr, .ca, .com.au, .in, and more
• Incremental monitor mode — KV watermarks; emit only new reviews/jobs or changed scores
• Compact mode — token-efficient rows for MCP / LLM pipelines
• HTTP-only — Chrome TLS impersonation, no headless browser; fail-fast on Cloudflare/DataDome
• Suite chain — enrich employers discovered via Arbeitsagentur or Stepstone

Use Cases

Use case	What you get
Employer due diligence	Overall rating, review count, culture snapshot before a hire or investment
Employer-brand monitoring	Newest public review snippets with titles, ratings, and job titles
Compensation benchmarking	Salary bands by title (median / p10–p90) when the salaries feed is available
Interview prep	Questions, difficulty, and offer outcomes when interview pages return data
Hiring-signal feed	Open roles + estimated pay + employer score
Multi-market research	Same employer on .com vs .de vs .co.uk

Quick Start

Company intel (name resolve):

{
  "companyNames": ["Amazon", "Google"],
  "domain": "com",
  "maxItems": 50,
  "includeReviews": true,
  "maxReviewsPerCompany": 20,
  "sortReviewsBy": "DATE",
  "includeJobs": true,
  "maxJobsPerCompany": 20,
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": ["RESIDENTIAL"],
    "apifyProxyCountry": "US"
  }
}

Keyword job search:

{
  "jobKeywords": ["software engineer"],
  "location": "New York, NY",
  "maxJobs": 50,
  "sortJobsBy": "date",
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": ["RESIDENTIAL"],
    "apifyProxyCountry": "US"
  }
}

Overview URL:

{
  "startUrls": [
    { "url": "https://www.glassdoor.com/Overview/Working-at-Amazon-EI_IE6036.htm" }
  ],
  "includeReviews": true,
  "maxReviewsPerCompany": 30
}

Input Parameters

Parameter	Type	Default	Description
companyNames	Array	—	Plain company names to resolve
startUrls	Array	—	Overview / Reviews / Jobs / Interview / Salary / job-search URLs
employerIds	Array	—	Numeric IDs (6036) or E6036
jobKeywords	Array	—	Keyword job search
location	String	—	City/region for job search
domain	String	com	Regional site (co.uk, de, fr, …)
language	String	domain default	iso3 review language (eng, deu, fra, …)
maxItems	Integer	100	Hard cap on all row types (0 = unlimited)
includeReviews	Boolean	false	Employee reviews
maxReviewsPerCompany	Integer	50	Cap per employer
sortReviewsBy	String	DATE	DATE (newest) or RELEVANCE
includeInterviews	Boolean	false	Interview experiences
maxInterviewsPerCompany	Integer	50	Cap per employer
includeSalaries	Boolean	false	Salary band rows
maxSalariesPerCompany	Integer	50	Cap per employer
includeJobs	Boolean	false	Open jobs for each employer
maxJobsPerCompany	Integer	50	Cap per employer
maxJobs	Integer	50	Cap per keyword search
remoteOnly	Boolean	false	Remote jobs filter
jobPostedWithinDays	Integer	—	Optional recency filter (1, 7, 30, …)
incrementalMode	Boolean	false	Emit only deltas vs KV baseline
compact	Boolean	false	Core fields only
proxyConfiguration	Object	US residential	Match country to domain

Output Format

Each dataset item has a type discriminator.

Type	Key fields
company	employerId, name, overallRating, reviewCount, recommendToFriendPct, ceoApprovalPct, culture sub-ratings, headquarters, industry, size, url
review	rating, title, pros, cons, advice, sub-ratings, jobTitle, location, isCurrentJob, reviewDate
interview	jobTitle, difficulty, experience, outcome, questions, processDescription
salary	jobTitle, median, min, max, payPercentiles, salaryCount, currency
job	title, location, salaryMin / salaryMax, employerScore, datePosted, url

Example — company row:

{
  "type": "company",
  "employerId": 6036,
  "name": "Amazon",
  "overallRating": 3.5,
  "reviewCount": 210876,
  "url": "https://www.glassdoor.com/Overview/Working-at-Amazon-EI_IE6036.htm"
}

Example — review row:

{
  "type": "review",
  "reviewId": "105203492",
  "companyName": "Amazon",
  "title": "Great learning opportunities but demanding workload",
  "rating": 4.0,
  "pros": "Great learning opportunities but demanding workload",
  "jobTitle": "Software Engineer",
  "reviewDate": "2026-08-17"
}

Example — job row:

{
  "type": "job",
  "jobId": "1010226886266",
  "title": "Fulfillment Center Warehouse Associate",
  "companyName": "Amazon",
  "location": "Modesto, CA",
  "salaryMin": 21.75,
  "salaryMax": 23.25,
  "url": "https://www.glassdoor.com/job-listing/fulfillment-center-warehouse-associate-amazon-JV_IC1146953_KO0,38_KE39,45.htm?jl=1010226886266"
}

Integration examples

Node.js

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('crawloop/glassdoor-scraper').call({
  companyNames: ['Amazon'],
  includeReviews: true,
  maxReviewsPerCompany: 20,
  maxItems: 30,
  proxyConfiguration: {
    useApifyProxy: true,
    apifyProxyGroups: ['RESIDENTIAL'],
    apifyProxyCountry: 'US',
  },
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items.slice(0, 5));

Python

from apify_client import ApifyClient

client = ApifyClient(token)
run = client.actor("crawloop/glassdoor-scraper").call(
    run_input={
        "companyNames": ["Amazon"],
        "includeReviews": True,
        "maxReviewsPerCompany": 10,
        "maxItems": 30,
        "proxyConfiguration": {
            "useApifyProxy": True,
            "apifyProxyGroups": ["RESIDENTIAL"],
            "apifyProxyCountry": "US",
        },
    }
)
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item.get("type"), item.get("name") or item.get("title") or item.get("jobTitle"))

cURL

curl "https://api.apify.com/v2/acts/crawloop~glassdoor-scraper/runs?token=$APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"companyNames":["Amazon"],"includeJobs":true,"maxItems":20}'

MCP and AI assistants

Use this Actor from AI tools via Apify MCP. Connect your Apify account, then call crawloop/glassdoor-scraper.

Example prompts:

• "Run Glassdoor Scraper for Amazon and Google, include the newest reviews, return ratings plus pros/cons as JSON"
• "Scrape Glassdoor software engineer jobs in New York and summarize pay ranges"
• "Chain Arbeitsagentur Jobs Scraper for Pflege in Berlin, take unique employers, enrich via Glassdoor Scraper"

Suite next step

1. Pull Germany public openings with Arbeitsagentur Jobs Scraper or DACH commercial listings with Stepstone Jobs Scraper
2. Deduplicate employer names
3. Enrich here — Glassdoor scores, reviews, interviews, and pay bands

For global review monitoring beyond employers, use Trustpilot Scraper.

FAQ

Do I need a Glassdoor login?
No. This Actor reads publicly accessible pages and JSON. It does not submit credentials or bypass give-to-get walls.

Why residential proxies?
Glassdoor fronts Cloudflare (and sometimes DataDome). Datacenter IPs are usually blocked. Match apifyProxyCountry to domain (US for .com, DE for .de, GB for .co.uk).

Can I scrape Glassdoor with Python or Node.js?
Yes — use the Apify client examples above, or call the Actor from an AI assistant via Apify MCP.

Can I search all Glassdoor jobs by keyword?
Yes — set jobKeywords and optional location. Company-mode includeJobs is per employer.

Which domain should I use?
Use the market whose reviews and jobs you need. Ratings and review language differ by site (.com vs .de vs .co.uk).

Is this a Glassdoor API?
There is no official public Glassdoor API for this data. This Actor is an HTTP Glassdoor API alternative that exports a dataset you can pipe into BI, ATS, or LLM tools.

Related Actors

Actor	Focus
Glassdoor Scraper ◄── you are here	Global employer reviews, interviews, salaries, jobs
Arbeitsagentur Jobs Scraper	Germany BA Jobsuche listings
Stepstone Jobs Scraper	DACH commercial job board
Trustpilot Scraper	Company review monitoring (global)