Glassdoor Job Data Scraper

Unlock Glassdoor's salary insights and company intelligence.

Glassdoor isn't just another job board—it's where employees share real salaries, rate their employers, and reveal company culture. This scraper extracts job listings enriched with salary ranges, company ratings, employee counts, and industry data that you won't find elsewhere. Perfect for salary benchmarking, competitive hiring analysis, and building data-driven recruitment tools.

🌟 Why choose this Actor?

Built for comprehensive Glassdoor job intelligence, this Actor provides reliable access to one of the world's largest job platforms.

Feature	Glassdoor Job Data Scraper	Bright Data	Zyte
Pricing Model	✅ $0.003/job	❌ $500+/month	❌ Enterprise only
No Commitment	✅ Pay-per-result	❌ Monthly contract	❌ Annual contract
Unified Schema	✅ Normalized output	✅ Yes	✅ Yes
Setup Complexity	✅ No-code, 1-click	⚠️ Technical setup	❌ Complex setup
Glassdoor Focus	✅ Specialized	⚠️ Generic	⚠️ Generic

🏆 Key Features

📊 Glassdoor-Specific Data Extraction

• 💵 Salary Ranges: Min/max compensation with currency and pay period (hourly/monthly/yearly)—Glassdoor's signature data.
• ⭐ Company Ratings: Aggregate employee satisfaction scores that influence candidate decisions.
• 👥 Company Size & Revenue: Employee headcount ranges and revenue brackets for company segmentation.
• 📝 Full Job Descriptions: Complete requirements, responsibilities, and qualifications in markdown format.
• 🌍 40+ Countries: Glassdoor's global presence from US and UK to Germany, India, and beyond.

🎯 Use Cases

💵 Compensation Intelligence

• Salary Benchmarking: Compare your offers against market rates using Glassdoor's crowdsourced salary data.
• Compensation Strategy: HR teams use this data to set competitive pay bands and reduce offer rejections.
• Negotiation Insights: Career coaches leverage salary ranges to help clients negotiate better packages.
• Pay Equity Audits: Analyze salary distributions across roles and locations for fair pay compliance.

🏢 Employer Brand Monitoring

• Competitor Hiring Radar: Track which roles competitors post and at what salary levels.
• Talent Market Mapping: Identify which companies are scaling (high job volume) vs. downsizing.
• Employer Comparison: Use company ratings and employee counts to benchmark against industry peers.

📈 Job Market Analytics

• Skills Demand Tracking: Analyze job descriptions to identify trending skills and emerging roles.
• Geographic Hotspots: Map hiring activity by location to spot talent hubs and remote-friendly employers.
• Industry Reports: Generate data-backed whitepapers on hiring trends and salary movements.

🤖 AI & Automation Pipelines

• Job Matching Engines: Feed structured data into ML models for candidate-job relevance scoring.
• Career Chatbots: Power conversational AI with real-time job and salary data from Glassdoor.
• ATS Enrichment: Augment your applicant tracking system with company intelligence and market rates.

💰 Pricing

Resource	Cost	Description
Actor Usage	$0.00001	Charged for Actor runtime. Cost depends on resource consumption during execution.
Job Details	$0.00315	Charged for each job posting scraped. Includes complete metadata such as salary, company, and location. This is a flat fee per job.

Example Cost Calculation:

• Scraping "Software Engineer" + "Data Analyst" + "Product Manager" in New York
• 3 keywords × 100 jobs = 300 results → 300 × $0.00315 = $0.95 total

🧜 How it Works

💻 Input Parameters

{
  "search_terms": ["Senior Data Scientist", "Machine Learning Engineer"],
  "country": "United States",
  "location": "San Francisco",
  "posted_since": "7 days",
  "max_results": 5000
}

Parameter	Type	Required	Description	Example
search_terms	string[]	✅	Keywords to search: job titles, skills, or company names	["Senior Data Scientist", "ML Engineer"]
country	string	✅	Target country for job search (40+ countries supported)	United States
location	string	❌	City or region within the country (optional)	San Francisco
posted_since	string	✅	Filter jobs posted within this period ("7 days", "1 months")	7 days
max_results	integer	✅	Number of jobs to fetch per keyword (min: 10)	5000

📤 Output Structure

{
  "processor": "https://apify.com/nextapi/glassdoor-job-data-scraper",
  "processed_at": "2025-11-26T10:15:00+00:00",
  "platform": "Glassdoor",
  "platform_url": "https://www.glassdoor.com/job-listing/senior-data-scientist-stripe-JL789456123",
  "official_url": "https://stripe.com/jobs/senior-data-scientist",
  "title": "Senior Data Scientist",
  "posted_date": "2025-11-24T00:00:00+00:00",
  "location": "San Francisco, CA",
  "is_remote": false,
  "description": "Join Stripe's Data Science team to build ML models that power global payments...\n\n## What you'll do\n- Build predictive models for fraud detection\n- Analyze payment patterns across 50+ countries\n- Partner with engineering to deploy models at scale",
  "job_type": "full-time",
  "job_level": "senior",
  "job_function": "Data Science",
  "listing_type": "standard",
  "emails": null,
  "skills": "Python, TensorFlow, SQL, Spark, A/B Testing",
  "work_from_home": "hybrid",
  "vacancy_count": 3,
  "experience_range": "5+ years",
  "salary_period": "yearly",
  "salary_minimum": 180000,
  "salary_maximum": 250000,
  "salary_currency": "USD",
  "company_name": "Stripe",
  "company_industry": "Financial Technology",
  "company_url": "https://www.glassdoor.com/Overview/Stripe-EI_IE671932",
  "company_website": "https://stripe.com",
  "company_logo": "https://media.glassdoor.com/sql/671932/stripe-logo.png",
  "company_addresses": "354 Oyster Point Blvd, South San Francisco, CA 94080",
  "company_revenue": "$1B - $10B",
  "company_description": "Stripe builds economic infrastructure for the internet, helping millions of businesses accept payments and manage operations online.",
  "company_rating": 4.3,
  "employee_count": "5000-10000",
  "review_count": 1892
}

📊 Output Fields Description

Job Information

Field	Type	Description
processor	string	URL of the Apify actor that processed this data
processed_at	string	ISO 8601 timestamp when the data was processed
platform	string	Source platform (Glassdoor)
platform_url	string	Job URL on Glassdoor
official_url	string	Direct link to company's job posting
title	string	Job position title
posted_date	string	Date when job was posted
location	string	Job location or city
is_remote	boolean	Whether the job allows remote work
description	string	Full job description in markdown format
job_type	string	Employment type (full-time, part-time, contract)
job_level	string	Seniority level (entry, mid, senior, executive)
job_function	string	Job category or function area
listing_type	string	Type of job listing (standard, featured, sponsored)
emails	string	Contact emails found in job posting
skills	string	Required skills and technologies
work_from_home	string	Work arrangement (remote, hybrid, on-site)
vacancy_count	integer	Number of open positions
experience_range	string	Required years of experience

Salary Information

Field	Type	Description
salary_period	string	Payment period (yearly, monthly, hourly)
salary_minimum	number	Minimum salary amount
salary_maximum	number	Maximum salary amount
salary_currency	string	Currency code (USD, EUR, GBP, etc.)

Company Information

Field	Type	Description
company_name	string	Name of the hiring company
company_industry	string	Industry sector of the company
company_url	string	Company profile URL on job platform
company_website	string	Official company website
company_logo	string	URL to company logo image
company_addresses	string	Company office locations
company_revenue	string	Annual revenue range
company_description	string	About the company
company_rating	number	Company rating score (out of 5)
employee_count	string	Number of employees
review_count	integer	Number of company reviews

🔌 Integrations

Seamlessly connect this actor to your existing pipelines via the Apify API.

🆔 Actor ID:

OFdvsjf7TqVYuQPky

Python Client

from apify_client import ApifyClient

client = ApifyClient("YOUR_API_TOKEN")
run = client.actor("nextapi/glassdoor-job-data-scraper").call(run_input={
    "max_results": 100,
    "posted_since": "1 months",
    "country": "United States",
    "location": "San Francisco",
    "search_terms": ["Python Developer", "Data Engineer"]
})

for job in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(f"{job['title']} at {job['company_name']} - ${job.get('salary_minimum', 'N/A')}")

Node.js Client

import { ApifyClient } from "apify-client";

const client = new ApifyClient({ token: "YOUR_API_TOKEN" });
const run = await client.actor("nextapi/glassdoor-job-data-scraper").call({
  max_results: 100,
  posted_since: "1 months",
  country: "United States",
  location: "San Francisco",
  search_terms: ["Python Developer", "Data Engineer"],
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((job) => console.log(`${job.title} at ${job.company_name}`));

🦜 LangChain

Use this actor as a document loader in LangChain to power your RAG pipelines with job market data for career advice chatbots.

🏗️ Metadata for Developers (JSON-LD)

{
  "@context": "https://schema.org",
  "@type": "SoftwareApplication",
  "name": "Glassdoor Job Data Scraper",
  "applicationCategory": "DeveloperApplication",
  "operatingSystem": "Cloud",
  "offers": {
    "@type": "Offer",
    "price": "0.00",
    "priceCurrency": "USD"
  },
  "description": "Scrape Glassdoor job listings with ease. Extract job titles, salaries, company details, descriptions, skills, and more. Features keyword search, location filtering, and structured output."
}

🚀 Performance Tips

Optimize your runs for speed, cost, and reliability with these best practices:

💰 Cost Optimization

• Start Small: Test with max_results: 10 and a single search term before scaling up.
• Monitor Costs: Check the "Usage" tab in Apify Console for real-time cost tracking. Each job costs $0.00315.
• Narrow Search: Use specific job titles instead of broad keywords to reduce irrelevant results.

⚡ Speed Optimization

• Fewer Keywords: Each search term creates a separate search. Use focused keywords for faster results.
• Regional Focus: Specify a location to reduce results and speed up processing.
• Recent Posts: Use shorter posted_since periods (e.g., "7 days") for faster results.

🛡️ Reliability Best Practices

• Valid Country: Ensure the country name matches exactly (e.g., "United States", not "USA").
• Monitor Progress: Use Apify Console's live log to track scraping progress.

📊 Data Quality Tips

• Salary Data: Not all jobs include salary info. Filter by salary_minimum field to get jobs with disclosed salaries.
• Fresh Data: Job postings change rapidly. Schedule daily runs for time-sensitive applications.
• Remote Jobs: Filter by is_remote: true or check work_from_home field for remote opportunities.

❓ FAQ

How to export job listings to Excel?

After the run completes, go to the Output tab in the Apify Console. Click the Export button and select Excel format. You will receive a neatly formatted spreadsheet with all job listings ready for analysis.

How do I search for remote jobs only?

Currently, the actor fetches all matching jobs. Filter the results by checking the is_remote field (boolean) or work_from_home field for remote/hybrid opportunities.

Why are some salary fields empty?

Not all job postings include salary information. Approximately 30-40% of jobs disclose salary ranges. Use the salary_minimum field to filter jobs with disclosed compensation.

How long does a typical scrape take?

Runtime depends on the number of search terms and max_results setting. A typical run with 2-3 keywords and 100 results completes in 1-3 minutes.

Why do some job titles not match my search keywords?

This is expected behavior. Glassdoor uses its own search algorithm that considers job relevance, not just exact keyword matching. The platform may return jobs based on:

• Related job titles and synonyms (e.g., "Developer" may return "Engineer" roles)
• Skills mentioned in job descriptions
• Industry and category associations
• Location-based relevance

This is the same behavior you would see when searching directly on Glassdoor.

⚖️ Legal & Compliance

This actor scrapes publicly available job postings only. It does not log in, access private data, or collect personal information of job seekers. You are responsible for adhering to each platform's Terms of Service and applicable privacy laws (GDPR/CCPA).

🏷️ Glassdoor Job Data Scraper

🔥 Search Terms: glassdoor scraper, glassdoor jobs api, glassdoor salary data, glassdoor company ratings, glassdoor employee reviews, salary transparency tool, employer ratings scraper, company culture data, glassdoor job listings, salary insights api, workplace ratings extractor, glassdoor data extraction, pay scale scraper, compensation data api, employer review scraper, glassdoor company data, job salary comparison, employee satisfaction data, glassdoor hiring data, company reputation scraper

💼 Use Cases: salary-benchmarking compensation-analysis employer-brand-research company-ratings-monitoring salary-transparency talent-market-intelligence competitive-pay-analysis hr-analytics employee-satisfaction-tracking workplace-culture-research hiring-trend-analysis offer-negotiation-data pay-equity-audit employer-comparison

🤝 Support & Community

• 📧 Support: Contact Us | 💬 Community: Telegram Group

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