Glassdoor Jobs Scraper

Glassdoor Jobs Scraper creates a structured dataset of job listings collected from Glassdoor, the employer-review and job-search platform. Each dataset item represents one job listing and can include job title, company, rating, location, posting age, apply link, salary estimate, and a description snippet, with optional detail-page enrichment for the full description, employer profile, skills, and geographic fields. Query the source by search keywords and location, control the result limit with maxItems, and retrieve records through the Apify Dataset API or export them as JSON, CSV, Excel, or another supported format.

Dataset at a glance

Property	Value
Source	glassdoor.com (job search; 10 country editions)
Record unit	One job listing
Input methods	Keyword search (searchQueries) + location, or search URLs (startUrls)
Main identifiers	listingId, jobUrl
Delivery	Apify Dataset and API
Export formats	JSON, CSV, Excel, XML, HTML (Apify dataset exports)
Update model	Fresh records per Actor run
Pricing	$1.00 per 1,000 jobs; +$2.00 per 1,000 for job details

Coverage and available records

The Actor collects jobs from public Glassdoor search results using one of two entry points:

• Search-based: Set searchQueries to job keywords (for example python or software engineer) and location to a country, state, or city. Leave searchQueries empty to list all jobs for the location.
• URL-based: Pass Glassdoor job-search URLs in startUrls to scrape those pages in addition to the search terms.
• Country editions: baseUrl selects one of ten Glassdoor editions (US, DE, UK, FR, NL, CA, AU, AT, IE, IN).

Record types and limits:

• Listing records are always collected: job title, company, rating, location, posting age, apply link, and description snippet.
• Detail fields are conditional: the full job description, employer profile, skills, and geographic coordinates are returned only when scrapeJobDetails is enabled, which fetches each job's detail data.
• Result cap: maxItems limits the number of jobs collected (0 means unlimited, the default). Collection stops after 500 result pages per search.

Known exclusions: the Actor collects jobs, not standalone company profiles (employer data is a byproduct of detail enrichment); content Glassdoor only shows behind login is not collected; each run captures page state at run time (no historical snapshots).

Data dictionary

Field names below match dataset record JSON properties exactly. Fields marked conditional appear only when scrapeJobDetails is enabled.

Field	Type	Nullable	Description	Example
listingId	integer	No	Glassdoor job identifier; best stable deduplication key	1010070316579
jobTitle	string	No	Job title as listed	JUNIOR GENAI ENGINEER (M/W/D)
normalizedJobTitle	string	Yes	Normalized job title	ingenieur (m/w/d)
companyName	string	No	Company name	Reply
companyId	integer	Yes	Glassdoor company identifier	306932
companyRating	number	Yes	Average company rating (0–5)	3.8
companyLogoUrl	string	Yes	Company logo image URL	https://media.glassdoor.com/sql/306932/reply-squareLogo-1680691862007.png
locationName	string	Yes	Job location as listed	Deutschland
locationId	integer	Yes	Glassdoor location identifier	96
ageInDays	integer	Yes	Posting age in days	134
easyApply	boolean	No	Whether the listing supports one-click apply	false
isSponsored	boolean	No	Whether the listing is sponsored	false
expired	boolean	No	Whether the listing has expired	false
url	string	No	Job listing URL	https://www.glassdoor.de/job-listing/...?jl=1010070316579
jobUrl	string	No	Same as url	Same as url
applyUrl	string	Yes	External apply link	https://www.glassdoor.de/partner/jobListing.htm?...
descriptionSnippet	string	Yes	Short description snippet	Als Junior GenAI Engineer...
jobAttributes	string[]	Yes	Attribute tags	["Azure", "Cloud-Architektur", ...]
sourceQuery	string	Yes	Search keyword that produced the record	python
searchQuery	string	Yes	Search keyword used	python
searchLocation	string	Yes	Location used in the search	Deutschland
salaryCurrency	string	Yes	Salary currency code	EUR
salaryPeriod	string	Yes	Salary period (ANNUAL, etc.)	ANNUAL
salaryMedian	number	Yes	Median salary estimate	65000
salaryP10	number	Yes	10th-percentile salary estimate	52000
salaryP90	number	Yes	90th-percentile salary estimate	81000

Detail-enriched fields (conditional — scrapeJobDetails):

Field	Type	Nullable	Description	Example
jobDescription	string	Yes	Full job description (HTML)	Long-form HTML
jobDescriptionText	string	Yes	Full job description (plain text)	Long-form text
employerIndustry	string	Yes	Employer industry	IT Services
employerSize	string	Yes	Employer size bucket	1000–5000
employerWebsite	string	Yes	Employer website URL	https://www.reply.com
employerHeadquarters	string	Yes	Employer headquarters	Turin, Italy
latitude	number	Yes	Job latitude	52.52
longitude	number	Yes	Job longitude	13.40
city	string	Yes	Job city	Berlin
state	string	Yes	Job state/region	Berlin
country	string	Yes	Job country	DE
skills	string[]	Yes	Skill tags	["Python", "Azure", ...]
education	string[]	Yes	Education requirements	["Bachelor's Degree"]
yearsOfExperience	string[]	Yes	Experience requirements	["3+ years"]
jobType	string[]	Yes	Employment types	["Full-time"]
jobDetails	object	Yes	Raw detail payload, with nested employerOverview, companyRatings, employerLinks, map, and other objects	See example record

Salary fields (salaryMedian, salaryP10, salaryP90) are estimates and are 0 or null when Glassdoor has no pay estimate for the listing.

Example dataset record

Real record produced with the input below (searchQueries: ["python"], location: "Deutschland", maxItems: 3, scrapeJobDetails: true).

{
  "listingId": 1010070316579,
  "jobTitle": "JUNIOR GENAI ENGINEER (M/W/D)",
  "normalizedJobTitle": "ingenieur (m/w/d)",
  "companyName": "Reply",
  "companyId": 306932,
  "companyRating": 3.8,
  "companyLogoUrl": "https://media.glassdoor.com/sql/306932/reply-squareLogo-1680691862007.png",
  "locationName": "Deutschland",
  "locationId": 96,
  "ageInDays": 134,
  "easyApply": false,
  "isSponsored": false,
  "expired": false,
  "url": "https://www.glassdoor.de/job-listing/junior-genai-engineer-m-w-d-reply-JV_IC5424598_KO0,23_KE306932.htm?jl=1010070316579",
  "jobUrl": "https://www.glassdoor.de/job-listing/junior-genai-engineer-m-w-d-reply-JV_IC5424598_KO0,23_KE306932.htm?jl=1010070316579",
  "applyUrl": "https://www.glassdoor.de/partner/jobListing.htm?jobListingId=1010070316579",
  "descriptionSnippet": "Als Junior GenAI Engineer ...",
  "jobAttributes": ["Azure", "Cloud-Architektur", "R"],
  "sourceQuery": "python",
  "searchQuery": "python",
  "searchLocation": "Deutschland",
  "salaryCurrency": "EUR",
  "salaryPeriod": "ANNUAL",
  "salaryMedian": 65000,
  "salaryP10": 52000,
  "salaryP90": 81000,
  "jobDescriptionText": "Als Junior GenAI Engineer ...",
  "employerIndustry": "IT Services",
  "employerSize": "1000–5000",
  "employerWebsite": "https://www.reply.com",
  "employerHeadquarters": "Turin, Italy",
  "latitude": 52.52,
  "longitude": 13.4,
  "city": "Berlin",
  "state": "Berlin",
  "country": "DE",
  "skills": ["Python", "Azure", "Machine Learning"]
}

The record above was produced with this input:

{
  "searchQueries": ["python"],
  "location": "Deutschland",
  "maxItems": 3,
  "scrapeJobDetails": true,
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": ["RESIDENTIAL"]
  }
}

Query and input reference

Input	Type	Required	Default	Accepted values	Description
searchQueries	array (stringList)	No	[]	Free-text job keywords	Job search keywords; empty lists all jobs for the location
location	string	No	Deutschland	Free-text country, state, or city	Job location as shown on Glassdoor
baseUrl	string	No	https://www.glassdoor.de	glassdoor.com/.de/.co.uk/.fr/.nl/.ca/.com.au/.at/.ie/.co.in	Glassdoor country edition
startUrls	array (requestListSources)	No	[]	Glassdoor job-search URLs	Extra search pages to scrape in addition to searchQueries
scrapeJobDetails	boolean	No	true	true / false	Fetch each job's detail data (charged as job details)
detailConcurrency	integer	No	8	1–50	Parallel detail requests
maxItems	integer	No	0	0 or any positive integer	Maximum jobs to collect; 0 = unlimited
proxyConfiguration	object	No	Apify proxy, RESIDENTIAL group	Apify proxy groups or custom proxies	Residential proxies are recommended

Minimal request:

{ "searchQueries": ["software engineer"], "location": "Berlin" }

Advanced request with detail enrichment:

{
  "searchQueries": ["data engineer"],
  "location": "Deutschland",
  "baseUrl": "https://www.glassdoor.de",
  "scrapeJobDetails": true,
  "detailConcurrency": 10,
  "maxItems": 500,
  "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": ["RESIDENTIAL"] }
}

Retrieve the data through the API

The Actor runs on the Apify platform, so there is no server to host and no crawling infrastructure to maintain.

1. Start the Actor with a JSON input (console or API).
2. Wait for the run to finish, or use a synchronous endpoint if you want the response inline.
3. Retrieve items from the run's default dataset.
4. Paginate or export the dataset.

Python example:

from apify_client import ApifyClient

client = ApifyClient("YOUR-APIFY-TOKEN")

run_input = {
    "searchQueries": ["software engineer"],
    "location": "Berlin",
    "maxItems": 20,
}

run = client.actor("datascrapers/glassdoor-jobs-scraper").call(run_input=run_input)
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item["listingId"], item["jobTitle"], item["companyName"])

Apify generates ready-to-run Python, JavaScript, and cURL examples on the Actor's API tab. Do not put a real API token in shared code or URLs.

Data quality and record handling

• Conditional fields: detail fields are present only when scrapeJobDetails is enabled. Listings alone return a leaner record.
• Salary fields: salaryMedian, salaryP10, and salaryP90 are estimates and are 0 or null when Glassdoor has no pay estimate for the listing.
• Source changes: Glassdoor page structure and values can change; unreadable fields are returned as null rather than fabricated.
• Deduplication: the Actor deduplicates listings within a run by listingId. Use listingId as the stable key and filter repeated runs against previously stored IDs.
• Detail fallback: detail fetches are best-effort; listing data is always returned even if detail enrichment fails.

Export and pipeline examples

Destination	Recommended method	Typical use
PostgreSQL / Supabase	Dataset API poll or webhook consumer	Store job listings alongside talent tables
Google Sheets	Apify Google Sheets integration	Share job shortlists with recruiting teams
CRM / ATS pipeline	Webhook on run completion	Push new listings into applicant tracking
S3 / cloud storage	Scheduled export via Apify scheduler + integration	Archival of labor-market snapshots

Pricing and cost examples

The Actor uses pay-per-event pricing with two chargeable events:

Event	Trigger	Rate (per 1,000 jobs)
Job result	Every job record pushed to the dataset	$1.00
Job details	scrapeJobDetails enabled, detail data fetched	$2.00

Example costs:

Records	Configuration	Estimated base cost
1,000	Listing only	$1.00
10,000	Listing only	$10.00
1,000	Listing + details	$3.00
10,000	Listing + details	$30.00

Apify paid plans reduce the per-1,000 rate (for example $0.80 per 1,000 jobs at the Gold tier). Compute units consumed by the run are billed by your Apify plan. Estimates depend on the verified pricing model and the options selected for the run.

Limitations and responsible data use

• The Actor collects publicly accessible data from Glassdoor job-search pages only, across ten supported country editions.
• The Actor collects jobs, not standalone company profiles; employer data is a byproduct of detail enrichment.
• Salary fields are estimates and are frequently absent when Glassdoor has no pay estimate.
• Collection stops after 500 result pages per search.
• Field availability depends on what Glassdoor renders at run time; some values can be null or missing, and site changes can alter fields.
• The Actor does not provide historical snapshots unless you store them yourself.
• You are responsible for compliance with Glassdoor's terms of service, applicable privacy law, and any contractual obligations before using the data.

Dataset questions

What does one dataset item represent?

One Glassdoor job listing, optionally enriched with its full detail data.

Which field should I use as a unique identifier?

listingId is the stable Glassdoor job identifier and is the recommended deduplication key. The jobUrl is a reasonable secondary key.

Are fields nullable or conditional?

Yes. Detail fields (full description, employer profile, skills, coordinates) exist only when scrapeJobDetails is enabled. Salary fields are 0 or null when Glassdoor has no pay estimate. Fields the listing does not render are returned as null.

Can I retrieve the records as CSV or JSON?

Yes. The dataset can be exported as JSON, CSV, Excel, XML, or HTML from the Apify Console, and queried through the Dataset API.

Does the Actor return historical data?

No. Each run captures the state of the listings at run time. To track salary or posting changes, schedule repeated runs and store the outputs yourself.

What counts as a billable result?

Two pay-per-event charges apply: a job-result charge for every job record ($1.00 per 1,000) and a job-details charge for each enriched job when scrapeJobDetails is enabled ($2.00 per 1,000).

Related datasets from Data Scrapers

• StepStone Jobs Scraper — Job listings from StepStone, useful for cross-board labor-market comparison.
• LinkedIn Company Scraper — Company profiles that can be joined with Glassdoor jobs by company name.
• LinkedIn Profile Scraper — Professional profiles for talent and hiring research.

Data Scrapers support

Need an additional field, record type, or export workflow? Contact Data Scrapers at stardustspotlight@gmail.com. Include a sample source URL, required fields, expected record volume, and preferred delivery format.