Glassdoor Jobs Scraper

What is Glassdoor Jobs Scraper?

Glassdoor Jobs Scraper extracts public Glassdoor job listings into a flat dataset with one row per job. Each row returns the job title, company name, company rating, location, Easy Apply flag, salary text with parsed minimum, maximum, currency and period, the job and apply URLs, and the search URL it came from. Recruiters, HR analytics teams, job-market researchers and AI agents use it for salary benchmarking, hiring-signal monitoring and sourcing, starting from a keyword and a location.

Why recruiters use this Glassdoor scraper

• Salary parsed for you. salaryText keeps the visible range, and salaryMin, salaryMax, salaryCurrency and salaryPeriod turn it into numbers you can sort and chart.
• Employer quality next to the role. companyRating shows the Glassdoor company rating on the same row as the job.
• Recency control. daysOld limits results to jobs posted in the last 1 to 30 days.
• Compensation-only datasets. Set includeNoSalaryJobs to false to keep only listings with visible pay.
• Clean, deduplicated rows. deduplicate removes repeats by job ID, URL or a title-company-location hash.
• Provenance on every row. sourceUrl, searchQuery, requestedLocation and scrapedAt record exactly where and when each job was collected.

Best fit and related Actors

Best fit for current Glassdoor job listings: salary benchmarking for a role in a city, tracking which companies are hiring, or giving an agent a fresh sample such as "25 software engineer jobs in New York with salaries and apply links". The Actor is designed for job-listing pages; company reviews and interview pages are separate Glassdoor surfaces.

• For employee reviews of the companies you find, continue with Glassdoor Reviews Scraper.
• When you want the same search across Indeed, LinkedIn and Glassdoor together, use Jobs Scraper instead.

Example workflow: from a role and city to a salary benchmark

A compensation analyst starts with searchQuery set to data engineer, location set to Austin, TX, daysOld set to 14 and includeNoSalaryJobs set to false. The dataset returns each job's title, companyName, companyRating, salaryMin, salaryMax and salaryPeriod. They normalize hourly ranges to annual, compare the median against their internal band, and export the table for the pay review. A weekly schedule with the same input shows how the market range moves over time.

How to scrape Glassdoor jobs

1. Enter a Job search query and a Job location, or paste Glassdoor jobs search URLs in Glassdoor jobs URLs.
2. Set Maximum jobs, and optionally Posted within days and Include jobs without salary.
3. Click Start, then export the dataset as JSON, CSV or Excel, or read it through the API.

Input

{
  "searchQuery": "software engineer",
  "location": "New York, NY",
  "country": "US",
  "maxResults": 50,
  "daysOld": 7,
  "includeNoSalaryJobs": true,
  "deduplicate": true
}

Field	Type	What it controls
searchQuery	string	Role, skill or company keywords. Default software engineer.
location	string	City, region or Remote. Default New York, NY.
country	string	Two-letter country label for output and summaries, such as US, GB, CA or AU.
startUrls	array	Glassdoor jobs search result URLs, scraped directly and taking priority over the query.
maxResults	integer	Maximum jobs to save, which is also the cap on billed job events. Default 50.
daysOld	integer	Only jobs posted within this many days, from 1 to 30.
includeNoSalaryJobs	boolean	Keep listings without a visible salary. Default true.
deduplicate	boolean	Skip repeated jobs within the run. Default true.
debug	boolean	Save captured responses to the key-value store for inspection. Default false.

Output

One dataset row per job.

Field	What it contains
jobId	Glassdoor job listing ID
title	Job title
companyName, companyRating	Hiring company and its Glassdoor rating
location	Job location or remote label
easyApply	true when the job supports Glassdoor Easy Apply
salaryText	Visible salary range, as shown
salaryMin, salaryMax	Parsed salary bounds
salaryCurrency, salaryPeriod	Currency code and period such as hour or year
jobUrl, applyUrl	Job listing link and apply link
searchQuery, requestedLocation, requestedCountry	The request that produced the row
source, sourceUrl, scrapedAt	Source name, search page URL and collection time

The schema also reserves datePosted, validThrough, employmentType, remoteType and description. Glassdoor search cards usually leave these as null, so use daysOld for recency and open jobUrl for the full description.

{
  "jobId": "1010265289757",
  "title": "Product Manager",
  "companyName": "Obie",
  "companyRating": 4.5,
  "location": "Remote",
  "remoteType": null,
  "employmentType": null,
  "easyApply": true,
  "salaryText": "$90K - $130K (Employer provided)",
  "salaryMin": 90000,
  "salaryMax": 130000,
  "salaryCurrency": "USD",
  "salaryPeriod": null,
  "datePosted": null,
  "validThrough": null,
  "description": null,
  "jobUrl": "https://www.glassdoor.com/job-listing/product-manager-obie-JV_KO0,15_KE16,20.htm?jl=1010265289757",
  "applyUrl": "https://www.glassdoor.com/job-listing/product-manager-obie-JV_KO0,15_KE16,20.htm?jl=1010265289757",
  "searchQuery": "product manager",
  "requestedLocation": "London",
  "requestedCountry": "GB",
  "source": "glassdoor",
  "sourceUrl": "https://www.glassdoor.com/Job/jobs.htm?sc.keyword=product+manager&locKeyword=London&locT=C&fromAge=7",
  "scrapedAt": "2026-10-01T12:36:29.756Z"
}

Each run also writes OUTPUT and RUN_SUMMARY records to the default key-value store with counts, duplicate skips and charged event totals. Their outcome field is COMPLETE, PARTIAL (some jobs saved, some search pages blocked), VALID_EMPTY (Glassdoor showed its own "no results" message), INVALID_INPUT, or UPSTREAM_FAILED (Glassdoor kept every search page behind a security check, so the run fails). The dataset only holds real job rows; run notes stay in these records.

Pricing

This Actor uses Pay per event with Apify platform usage included in the event price. You pay one Job scraped event for each job saved to the dataset and one Actor Start event per run. Duplicates that deduplicate removes are skipped before billing, and maxResults caps the number of job events. A run that saves no jobs makes no job charges.

Worked example in words: a run with maxResults set to fifty that saves fifty jobs costs fifty Job scraped events plus one Actor Start event. Check the live Pricing tab on this page for the current event prices, and set a maximum charge per run to cap spend.

API example

curl -X POST "https://api.apify.com/v2/acts/khadinakbar~glassdoor-jobs-scraper/run-sync-get-dataset-items?token=YOUR_API_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"searchQuery": "data engineer", "location": "Austin, TX", "maxResults": 25, "daysOld": 7}'

from apify_client import ApifyClient

client = ApifyClient("YOUR_API_TOKEN")
run = client.actor("khadinakbar/glassdoor-jobs-scraper").call(run_input={
    "searchQuery": "product manager",
    "location": "San Francisco, CA",
    "maxResults": 50,
    "includeNoSalaryJobs": False,
})
for job in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(job["title"], job["companyName"], job["salaryMin"], job["salaryMax"])

Use with AI agents (MCP)

Connect the Actor to Claude, ChatGPT, Cursor or any MCP client through Apify MCP and ask:

Find 25 software engineer jobs in New York posted in the last week on Glassdoor. Return title, company, rating, salary range and apply link, and tell me the median salary.

The agent sets searchQuery, location, daysOld and maxResults, reads rows back from the dataset, and cites each job by jobUrl and scrapedAt. maxResults keeps the cost scope fixed before the run starts.

Best results

Starting situation	Helpful action	Expected outcome
Salary benchmarking	Set includeNoSalaryJobs to false	Every row has a salary range
Recent hiring signals	Set daysOld to 7	Jobs posted in the last week
A saved Glassdoor search	Paste the results URL in startUrls	The same filters you set on Glassdoor
Remote roles	Set location to Remote	Remote-labelled listings
Mixed hourly and annual pay	Group by salaryPeriod before comparing	Like-for-like salary figures
Non-US markets	Set country and a local location such as London	Correctly labelled rows for that market

Builder's note

I built this Actor around the questions recruiters ask first: who is hiring, where, and for how much. That is why salary is parsed into numeric columns and the company rating sits on the same row. I designed maxResults as both the output cap and the billing cap, so the cost of a run is known before it starts, and I kept every row tied to its search URL so results stay easy to audit.

FAQ

Do I need a Glassdoor account?

No. The Actor collects public job listings with no login or cookies.

Can I filter by salary?

Set includeNoSalaryJobs to false to keep only jobs with a visible range, then filter on salaryMin and salaryMax.

Does it work outside the US?

Yes. Set location to a city such as London or Toronto and country to the matching two-letter code.

Where are company reviews and interview questions?

Those live on separate Glassdoor pages. Use Glassdoor Reviews Scraper for employee reviews.

Responsible use

This Actor collects public job-listing information from Glassdoor. Use it for lawful recruiting and labor-market research, review Glassdoor's terms of service and applicable laws before large runs or redistribution, and handle any personal data in line with privacy laws such as the GDPR and CCPA. Glassdoor is a trademark of its owner; this independent Actor is not affiliated with or endorsed by Glassdoor.