# Glassdoor Jobs Scraper (`dan-horton/glassdoor-jobs-scraper`) Actor

Scrape Glassdoor jobs with full descriptions, salary figures labelled by source, and no charge for duplicate results. $1 per 1,000 jobs.

- **URL**: https://apify.com/dan-horton/glassdoor-jobs-scraper.md
- **Developed by:** [Dan Horton](https://apify.com/dan-horton) (community)
- **Categories:** Jobs, Lead generation, Developer tools
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $1.00 / 1,000 job scrapeds

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## Glassdoor Jobs Scraper

Scrape Glassdoor job listings with full job descriptions, salary ranges that
tell you where each figure came from, and no charge for duplicate results.

**$1 per 1,000 jobs.** Full descriptions are an optional add-on at $5 per 1,000.

### What you get

One row per job. Every field is present on every row, with `null` where
Glassdoor has no value — so your downstream code can rely on the shape.

`jobId` · `title` · `companyName` · `companyRating` · `location` · `isRemote` ·
`salaryMin` · `salaryMax` · `salaryCurrency` · `salaryPeriod` · `salarySource` ·
`isEasyApply` · `postedAt` · `jobUrl` · `companyUrl` · `descriptionSnippet` ·
`descriptionText` · `descriptionHtml` · `scrapedAt`

Measured across a 1,000-job run: 100% coverage on titles, companies, locations,
URLs and posting dates. 94.7% on company rating. 91.7% on salary.

### Full job descriptions

Switch on `fetchFullDescriptions` and every row carries the complete posting
text — about 4,900 characters on average, up to 18,000 — as both plain text and HTML.

Glassdoor's search results carry only a ~120-character preview. The full text
lives on each job's own page, which means a separate fetch per job. So you get
the preview in `descriptionSnippet` and the full text in `descriptionText`, and
`descriptionText` stays `null` when you haven't asked for it. A truncated
description never masquerades as a complete one.

Because each description is its own page fetch, it is priced separately and off
by default. A 1,000-job run with descriptions takes about an hour.

### Salary you can check

`salarySource` tells you whether each figure came from the employer or from
Glassdoor's own estimate. In a 1,000-job sample: 548 rows employer-provided,
369 estimated.

Salary analysis built on unlabelled data is analysis built on a mix of stated
facts and models, with no way to tell them apart. This field is how you tell
them apart.

### You are not charged for duplicates

Glassdoor recycles listings across pages and across searches. A typical run
collects 200-250 repeats. This scraper drops them and does not bill you for
them.

Charges fire per unique job written to your dataset — never per request, never
for a page that failed, never for a row that came back empty. `maxItems` is a
hard ceiling: the run stops there and stops charging there.

### How many jobs one search returns

Glassdoor stops serving new results for a single search after roughly 30-90
jobs, then repeats listings it has already shown. That is Glassdoor's limit, not
this scraper's, and every Glassdoor scraper meets it.

To collect more, pass several entries in `searchQueries`. Narrower titles and
separate locations each get their own window of results, and duplicates across
them are removed automatically. A 1,000-job run typically needs 30-40 searches.

If a run falls short, it tells you how many pages it read, how many unique jobs
it found, and why it stopped. It does not truncate silently.

### Locations

Cities, states and whole countries. Pass a place name in `location` and it is
resolved against Glassdoor's own location index rather than a built-in list, so
there is no fixed set of supported countries.

Verified in the United States, United Kingdom, Germany, Canada, India, the
Netherlands and Australia.

### Pricing

| Event | Price |
| --- | --- |
| Job scraped | $0.001 — $1 per 1,000 |
| Full description fetched | $0.005 — $5 per 1,000 |

Each run costs $0.00005 to start. Beyond that you pay only for unique jobs
saved to your dataset — duplicates, failed pages and blocked requests are free.

### Maintenance

Glassdoor changes its site, and when it does, scrapers break. This one is
maintained: report a problem through the Issues tab and it gets fixed.

# Actor input Schema

## `searchQueries` (type: `array`):

Job titles or keywords to search for. The Actor runs every query and combines the results.

## `location` (type: `string`):

City or location to search in, e.g. 'New York, NY'. Leave empty to search everywhere (remote included).

## `countryCode` (type: `string`):

Two-letter ISO country code for the Glassdoor country site. Leave empty for the US site.

## `maxItems` (type: `integer`):

Maximum number of jobs to scrape. This is your cost ceiling: pricing is $1 per 1,000 jobs (plus $0.005 per full description if fetchFullDescriptions is enabled). The run stops cleanly once this many jobs have been scraped or your spending limit is reached.

## `datePosted` (type: `string`):

Only return jobs posted within this time window.

## `minCompanyRating` (type: `number`):

Only return jobs from companies rated at least this many stars (1-5). Leave empty for no filter.

## `easyApplyOnly` (type: `boolean`):

Only return jobs that support Glassdoor easy apply.

## `fetchFullDescriptions` (type: `boolean`):

Fetch the full job description for every job (descriptionText and descriptionHtml). With this off, only a short descriptionSnippet is included and descriptionText/descriptionHtml are null. WARNING: fetching full descriptions makes ~1 extra request per job and takes about an hour per 1,000 jobs, and each fetched description is billed $0.005 via the job-description-fetched event.

## `proxyConfig` (type: `object`):

Apify Unblocker is used by default - it is the only transport that reliably passes Glassdoor's Cloudflare anti-bot wall (residential proxies alone get challenged). You can also provide your own custom proxy URLs.

## Actor input object example

```json
{
  "searchQueries": [
    "data engineer",
    "software engineer",
    "data scientist"
  ],
  "location": "New York, NY",
  "maxItems": 50,
  "datePosted": "anyTime",
  "minCompanyRating": null,
  "easyApplyOnly": false,
  "fetchFullDescriptions": false,
  "proxyConfig": {
    "useApifyProxy": true,
    "apifyProxyGroups": [
      "UNBLOCKER"
    ]
  }
}
```

# Actor output Schema

## `jobs` (type: `string`):

Dataset of scraped job listings. Use the Overview view for the recruiter scan layout.

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "searchQueries": [
        "data engineer",
        "software engineer",
        "data scientist"
    ],
    "location": "New York, NY",
    "maxItems": 50,
    "fetchFullDescriptions": false,
    "proxyConfig": {
        "useApifyProxy": true,
        "apifyProxyGroups": [
            "UNBLOCKER"
        ]
    }
};

// Run the Actor and wait for it to finish
const run = await client.actor("dan-horton/glassdoor-jobs-scraper").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "searchQueries": [
        "data engineer",
        "software engineer",
        "data scientist",
    ],
    "location": "New York, NY",
    "maxItems": 50,
    "fetchFullDescriptions": False,
    "proxyConfig": {
        "useApifyProxy": True,
        "apifyProxyGroups": ["UNBLOCKER"],
    },
}

# Run the Actor and wait for it to finish
run = client.actor("dan-horton/glassdoor-jobs-scraper").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "searchQueries": [
    "data engineer",
    "software engineer",
    "data scientist"
  ],
  "location": "New York, NY",
  "maxItems": 50,
  "fetchFullDescriptions": false,
  "proxyConfig": {
    "useApifyProxy": true,
    "apifyProxyGroups": [
      "UNBLOCKER"
    ]
  }
}' |
apify call dan-horton/glassdoor-jobs-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,dan-horton/glassdoor-jobs-scraper"
        }
    }
}

```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/Xpe2iu23Uxhq33exT/builds/khhbkebfZBnZMQBj0/openapi.json