Glassdoor Jobs Scraper

Glassdoor Jobs Scraper

The Glassdoor Jobs Scraper extracts structured job listings and company insights from regional Glassdoor sites at scale — a fast, reliable way to scrape Glassdoor job listings for recruiters, analysts, and growth teams. It solves the manual copy‑paste problem by returning clean, typed fields so you can build dashboards, enrich pipelines, or export datasets for analysis. This Glassdoor job postings scraper doubles as a Glassdoor jobs API alternative, built in Python, and designed for automated Glassdoor job search scraping at scale.

What data / output can you get?

Below are examples of structured fields the scraper saves to the Apify dataset (exportable to JSON or CSV). Each row represents one job, with both job and employer details.

Data field	Description	Example value
job_title	Visible title of the job	“Software Engineer”
job_id	Unique listing ID parsed from the job link	“1234567890”
job_url	Absolute URL to the job details	“https://www.glassdoor.com/job-listing/…”
job_location.city	Parsed city when available	“san francisco”
job_location.country	ISO-like country code when available	“us”
job_posted_date	ISO date derived from discoverDate or ageInDays	“2026-04-20”
job_remote	Remote/WFH flag inferred from attributes	true
job_salary.pay_period	Pay period text (normalized lower-case)	“year”
job_salary.currency	ISO currency code if present	“USD”
job_benefits_tags	Extracted benefits tags from attributes/highlights	[“health insurance”, “401(k)”]
job_job_types	Job type(s) inferred from Indeed codes or header	[“fulltime”]
company_name	Employer name from overview/header	“Acme Corp”
company_url	Employer overview page URL	“https://www.glassdoor.com/Overview/Working-at-Acme…”
company_sizes_str	Company size string from overview	“1001 to 5000 Employees”
job_description	Clean, plain‑text description	“We are looking for a Software Engineer who…”
all	Raw job payload enriched with employer awards	{ …full JSON… }

Bonus: You also get fields like job_description_html, job_sponsored, job_industry, job_language, company_logo, company_headquarters_location, company_revenue, company_website, company_industries, and company_uri_providers. Results are saved to the Apify dataset, ready to download as JSON or CSV.

Key features

• 🚀 Robust BFF + employer enrichment Queries Glassdoor’s job-search BFF endpoint and enriches results with employer overview data, so you capture both listings and deeper company context.

• 🎯 Powerful filtering Apply filters for salary range, listing freshness, company substring, industry, domain, employer size, job type, seniority, remote‑only, radius, and minimum employer rating — all from a single run.

• 🌍 Regional site support Choose from multiple Glassdoor country sites (e.g., us, gb, de, fr, es, in, jp, kr, and more) to focus your search where it matters.

• 🧭 No login required Works on public job listings without cookies or authentication.

• 🔄 Live dataset push Each job row is pushed as soon as it’s built, so you can start reviewing and exporting immediately.

• 🧠 Reliability via smart connection ladder Automatic escalation from direct → Apify DATACENTER → Apify RESIDENTIAL, with sticky residential after the first residential success for stable throughput.

• 🧪 Developer‑friendly, Python-powered Built with Apify’s Python runtime and AsyncSession for performance. Access your data programmatically via Apify’s API, or wire it into your data pipelines as a Glassdoor jobs scraper Python workflow.

How to use Glassdoor Jobs Scraper - step by step

1. Create or log in to your Apify account.
2. Open the Glassdoor Jobs Scraper on the Apify platform.
3. In the input form, set your core search:
   • keyword: the role or skills you’re targeting (e.g., “Software Engineer”).
   • country: pick the regional Glassdoor site (e.g., us, gb, de).
4. Optional — refine your search:
   • location, salary range (minSalary, maxSalary), fromAge, jobType, radius, industryType, domainType, employerSizes, applicationType, remoteWorkType, seniorityType, minRating.
5. Optional — proxyConfiguration:
   • Leave off for direct connection, or configure Apify Proxy for added reliability.
6. Click Start to run the scraper. Watch logs for live progress as jobs are discovered and saved.
7. When finished, go to the Dataset tab to view results. Export your data as JSON or CSV for analysis or downstream workflows.

Pro Tip: Use the Apify API to schedule runs, fetch datasets programmatically, and integrate this Glassdoor job board scraper into your data pipelines as a Glassdoor jobs API alternative.

Use cases

Use case	Description
Recruitment pipeline enrichment	Aggregate current openings by title, location, employer size, and benefits to prioritize outreach and fill roles faster.
Market and competitor research	Track hiring signals by domain and industry to map where competitors are investing and expanding geographically.
Salary range benchmarking	Filter to listings with pay data and analyze job_salary fields to benchmark compensation by location and seniority.
Remote hiring analysis	Apply the remote-only filter to measure distributed hiring trends across roles and countries.
Data analytics & dashboards	Export CSV/JSON to BI tools and create time-series dashboards on job volumes, industries, and rating thresholds.
Academic & labor studies	Collect structured data for longitudinal studies on job markets, domains, and employer characteristics.
API pipelines & automation	Use Apify’s API to trigger runs and pull datasets into ETL workflows as a Glassdoor jobs crawler component.

Why choose Glassdoor Jobs Scraper?

Purpose‑built for precision, scale, and reliability, this Glassdoor jobs scraper delivers clean, structured outputs with production‑ready robustness.

• ✅ Structured accuracy: Normalized fields for locations, salary meta, benefits, job types, and employer info.
• 🌍 Global coverage: Target multiple regional Glassdoor sites with one tool.
• 📈 Scalable filtering: Fine‑tune salary, age, remote, industry, and more for high‑signal datasets.
• 🧰 Developer access: Drive runs and consume results via the Apify API in your Python workflows.
• 🛡️ Built‑in resilience: Smart proxy ladder (direct → DATACENTER → RESIDENTIAL) and sticky residential for consistent results.
• 💸 Cost‑effective automation: Export datasets to CSV/JSON and avoid fragile browser extensions or one‑off scripts.
• 🔌 Workflow‑ready: Designed for hands‑off data extraction to power recruitment, research, and analytics pipelines.

Bottom line: a reliable Glassdoor jobs scraper tool that outperforms ad‑hoc scripts and unstable alternatives.

Is it legal / ethical to use Glassdoor Jobs Scraper?

Yes — when used responsibly. This actor collects publicly available job listings and employer information. You should:

• Scrape only public data and respect Glassdoor’s terms of use.
• Comply with applicable regulations (e.g., GDPR, CCPA) when storing or processing data.
• Avoid collecting or using private, authenticated, or personal data beyond what’s publicly available.
• Consult your legal team for edge cases or jurisdiction‑specific requirements.

Input parameters & output format

Example JSON input

{
  "keyword": "Software Engineer",
  "maxItems": 200,
  "country": "us",
  "location": "San Francisco, CA",
  "includeNoSalaryJob": false,
  "companyName": "Acme",
  "minSalary": 100000,
  "maxSalary": 180000,
  "fromAge": "7",
  "jobType": "fulltime",
  "radius": "18",
  "industryType": "INFORMATION_TECHNOLOGIE",
  "domainType": "ENGENERING",
  "employerSizes": "MEDIUM",
  "applicationType": "EASY_APPLY_INCLUDED",
  "remoteWorkType": "REMOTE_ONLY",
  "seniorityType": "entrylevel",
  "minRating": "3",
  "proxyConfiguration": {
    "useApifyProxy": false
  }
}

Input fields

Field	Type	Description	Default	Required
keyword	string	Role, skills, or title for the search (used with country).	—	No
maxItems	integer	Maximum number of jobs to collect per run (1–500).	200	No
country	string	Regional Glassdoor site to target (e.g., us, gb, de, fr, es, in, jp, kr, etc.).	"us"	No
location	string	Optional city/region text to focus results (resolved via Glassdoor location AJAX).	""	No
includeNoSalaryJob	boolean	Include listings without pay information when true.	false	No
companyName	string	Filter by employer name substring.	""	No
minSalary	integer	Minimum salary filter in the site’s local currency.	0	No
maxSalary	integer (nullable)	Maximum salary filter in the site’s local currency; set 0 or omit for no cap.	—	No
fromAge	string (enum)	Listing freshness: ANY, 1, 3, 7, 14, 30 (days).	"ANY"	No
jobType	string (enum)	Contract/work style: all, fulltime, parttime, contract, temporary, temp-to-hire, internship, entrylevel, apprenticeship.	"all"	No
radius	string (enum)	Search radius in km around location: "0","6","12","18","31","62","124".	"18"	No
industryType	string (enum)	Industry sector filter, or ALL for everything.	"ALL"	No
domainType	string (enum)	Job family/domain filter, or ALL for everything.	"ALL"	No
employerSizes	string (enum)	Employer size filter: ALL, TINY, SMALL, MEDIUM, LARGE, HUGE.	"ALL"	No
applicationType	string (enum)	Application flow: ALL, EASY_APPLY_INCLUDED, EASY_APPLY_ONLY.	"ALL"	No
remoteWorkType	string (enum)	Remote filter: ANY or REMOTE_ONLY.	"ANY"	No
seniorityType	string (enum)	Seniority stage: all, internship, entrylevel, midseniorlevel, director, executive.	"all"	No
minRating	string (enum)	Minimum employer rating: "0"–"5".	"0"	No
proxyConfiguration	object	Optional Apify Proxy settings for reliability and georouting.	{ "useApifyProxy": false }	No

Example JSON output

{
  "job_title": "Software Engineer",
  "job_id": "1234567890",
  "job_normalized_title": "software engineer",
  "job_url": "https://www.glassdoor.com/job-listing/software-engineer-JV_IC1147401_KO0,17.htm?jobListingId=1234567890",
  "job_location": {
    "unknown": "San Francisco, CA",
    "city": "san francisco",
    "country": "us",
    "zip": "94105"
  },
  "job_description": "We are looking for a Software Engineer who will build...",
  "job_description_html": "<p>We are looking for a Software Engineer...</p>",
  "job_posted_date": "2026-04-20",
  "job_remote": true,
  "job_salary": {
    "currency": "USD",
    "currency_symbol": "$",
    "pay_period": "year",
    "estimated": false
  },
  "job_candidate_numbers": null,
  "job_job_types": ["fulltime"],
  "job_levels": "entry level",
  "job_benefits_tags": ["health insurance", "401(k)"],
  "job_shifts_and_schedule_tags": ["day shift"],
  "job_sponsored": false,
  "job_industry": "Information Technology",
  "job_language": "en",
  "job_poster_first_name": null,
  "job_poster_last_name": null,
  "job_poster_linkedin_profile_url": null,
  "company_uri_providers": [
    {
      "provider": "glassdoor",
      "url": "https://www.glassdoor.com/Overview/Working-at-Acme-EI_IE12345.htm"
    }
  ],
  "company_name": "Acme Corp",
  "company_short_name": "Acme",
  "company_logo": "https://media.glassdoor.com/sqll/12345/acme-squarelogo.png",
  "company_headquarters_location": {
    "city": "san francisco",
    "unknown": "San Francisco, CA"
  },
  "company_sizes_str": "1001 to 5000 Employees",
  "company_size": null,
  "company_website": "https://www.acme.com",
  "company_revenue": "$500 million to $1 billion (USD)",
  "company_url": "https://www.glassdoor.com/Overview/Working-at-Acme-EI_IE12345.htm",
  "company_description": "Acme Corp is a global technology company...",
  "company_tag_line": "Building the future.",
  "company_linkedin_follower_count": null,
  "company_industries": ["Information Technology"],
  "company_locations": null,
  "all": {
    "...": "Full enriched jobview payload with awards and employer details"
  }
}

Notes:

• Some fields may be null or “Unknown” when not present on the source page (e.g., job_candidate_numbers, company_size, job_description_html).
• job_location fields depend on what Glassdoor provides; when parsing is not possible, unknown retains the original location string.

FAQ

Do I need to log in to use this Glassdoor Jobs Scraper?

No. The scraper works on publicly available listings and does not require authentication or cookies.

Can I filter by salary, remote, or employer rating?

Yes. You can set minSalary/maxSalary, choose REMOTE_ONLY via remoteWorkType, and filter by minRating to focus on higher‑rated employers.

How many jobs can I collect per run?

You control this with maxItems, up to 500 per run. Each run stops after collecting up to the specified number of matching jobs.

Which Glassdoor regions are supported?

Multiple regional sites are supported via the country parameter (for example: us, gb, de, fr, es, in, jp, kr, and more).

What export formats are available?

Results are saved to the Apify dataset and can be downloaded in JSON or CSV.

What data points are included for each job?

You’ll receive job fields (title, id, URL, location, description, salary meta, job types, benefits, remote flag, posted date), company fields (name, URL, size, revenue, HQ, website, industries), and the all field with the enriched raw payload.

Is this a Glassdoor jobs API alternative?

Yes. It serves as a reliable Glassdoor job data extraction workflow that you can drive via Apify’s API, making it a practical API alternative for many use cases.

Is this tool built in Python?

Yes. The Glassdoor jobs scraper Python implementation runs on Apify’s Python runtime and uses asynchronous requests for performance.

Closing thoughts

The Glassdoor Jobs Scraper is built for structured, scalable job data extraction from regional Glassdoor sites. With powerful filters, employer enrichment, and a resilient connection strategy, it helps recruiters, analysts, developers, and researchers turn job ads into actionable datasets. Export to JSON/CSV, automate via the Apify API, and integrate this Glassdoor careers scraper into your pipelines as a dependable Glassdoor jobs API alternative. Start extracting smarter job insights at scale today.