# β‘ Google Jobs Scraper (`veeronica/google-jobs-scraper`) Actor
Scrape Google Jobs listings by keyword and location. Get titles, companies, locations, salaries, posting dates, employment types, descriptions, and every apply link as clean JSON β no login or API key needed.
- **URL**: https://apify.com/veeronica/google-jobs-scraper.md
- **Developed by:** [Veronica](https://apify.com/veeronica) (community)
- **Categories:** Jobs, Automation, Lead generation
- **Stats:** 3 total users, 2 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet
## Pricing
from $10.00 / 1,000 job listings
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/platform/actors/running/actors-in-store#pay-per-event
## What's an Apify Actor?
Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases.
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.
In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md):
```bash
npm install apify-client
```
In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md):
```bash
pip install apify-client
```
In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md):
````bash
# MacOS / Linux
curl -fsSL https://apify.com/install-cli.sh | bash
# Windows
irm https://apify.com/install-cli.ps1 | iex
```bash
In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md).
If your project is in a different language, use 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
## Google Jobs Scraper
Google Jobs Scraper **extracts job listings from Google Jobs** β title, company, location, posting date, salary, employment type, description, and every apply link β and downloads them as **JSON, CSV, Excel, or XML**. It runs in the cloud, needs no coding, and **no login or API key**.
Try it right away: type the roles you're searching for and where, click **Start**, and watch the dataset fill up with structured job data.
### What data does it extract?
Each result is **one job listing**:
| Data | Details |
|---|---|
| πΌ **Job** | title, employment type, posting date and "time ago", and whether it's remote |
| π’ **Company** | nested `company` object: name and logo |
| π **Location** | where the job is based, as shown by Google |
| π **Source** | the job board the listing was aggregated from (e.g. LinkedIn, Indeed) |
| π° **Salary** | pay or salary range, when one is shown |
| π **Description** | the job description text shown on the card |
| πͺ **Apply options** | every place you can apply β label and outbound URL |
### How do I scrape Google jobs?
1. **Say what you want** β add one or more *Search queries* (a job title or skill) and a *Location*.
2. **Narrow it down** *(optional)* β filter by employment type, date posted, and remote-only.
3. **Pick a country** β the country/region to search. Set it to match your Location.
4. **Set how many** β choose *Maximum jobs*, or use `0` for no limit.
5. **Click Start** β then download the results from the **Storage** tab in any format, or send them anywhere with integrations.
### Input example
```json
{
"queries": ["software engineer", "data scientist"],
"location": "New York, United States",
"country": "us",
"language": "en",
"maxItems": 50,
"jobType": "fulltime",
"datePosted": "pastWeek",
"remote": false
}
````
### Output example
```json
{
"id": "go-rRRkq2ZVLnG404rgAAAAAA==",
"query": "software engineer",
"title": "Embedded Software Engineer",
"company": {
"name": "ALTEN",
"logo": "https://encrypted-tbn0.gstatic.com/images?q=β¦"
},
"location": "New York, NY",
"source": "Indeed",
"postedAt": "4 days ago",
"postedDate": "2026-06-11",
"employmentType": "Full-time",
"salary": null,
"remote": false,
"description": "Company Description ALTEN is a global engineering and technology consultancyβ¦",
"applyOptions": [
{ "title": "Apply directly on Indeed", "link": "https://www.indeed.com/viewjob?jk=β¦" }
]
}
```
### Input reference
| Field | Type | Description |
|---|---|---|
| `queries` | array | Job titles or skills to search for. Each is searched on its own. **Required.** |
| `location` | string | City, region, or country to search in. |
| `country` | string | Country/region to search (ISO-2). Set it to match your Location. Default `us`. |
| `language` | string | 2-letter language code for the results. Default `en`. |
| `maxItems` | integer | Total jobs to return across all queries. `0` = no limit. Default `50`. |
| `jobType` | string | One of `fulltime`, `parttime`, `internship`, `contract`. |
| `datePosted` | string | `any`, `past24h`, `past3Days`, `pastWeek`, or `pastMonth`. Default `any`. |
| `remote` | boolean | Return only remote / work-from-home jobs. Default `false`. |
### Why scrape Google jobs?
- **Job-market research** β track demand for roles, skills, and titles across regions.
- **Aggregation** β Google Jobs pools postings from many boards, so one search spans LinkedIn, Indeed, and more.
- **Recruiting & sourcing** β monitor who's hiring and where.
- **Salary benchmarking** β gather pay ranges where they're disclosed.
### Pricing
This Actor uses **pay-per-event** pricing: a small fee when a run starts, plus a fee per job delivered. You only pay for the listings you actually receive β set *Maximum jobs* to control your spend.
### Notes
- Runs through Apify Proxy automatically for reliable scraping β no proxy setup needed on your end.
- Uses **public** Google job results β the same data anyone can see. It does not log in or access private data.
- Job coverage depends on what Google shows for each search and region; some regions (e.g. the EU) don't surface job results.
- Make sure your use of the data complies with Google's terms and applicable laws.
# Actor input Schema
## `queries` (type: `array`):
Job titles, skills, or roles to search for β exactly what you'd type into Google's job search box (e.g. software engineer, registered nurse, product manager). Each query is searched on its own.
## `location` (type: `string`):
City, region, or country to search in (e.g. New York, London, Remote). Appended to each query as "β¦ near \". Leave empty to let Google decide from the country.
## `country` (type: `string`):
Which country/region to search from. Set this to match your Location. Note: Google does not surface job results in some regions, including the EU.
## `language` (type: `string`):
2-letter language code for the results (e.g. en, fr, es).
## `maxItems` (type: `integer`):
How many job listings to return in total (across all queries). Use 0 for no limit.
## `jobType` (type: `string`):
Restrict results to a single employment type. Leave empty to include all types.
## `datePosted` (type: `string`):
Only return jobs posted within this time window.
## `remote` (type: `boolean`):
Only return remote / work-from-home jobs.
## Actor input object example
```json
{
"queries": [
"software engineer"
],
"location": "New York, United States",
"country": "us",
"language": "en",
"maxItems": 50,
"datePosted": "any",
"remote": false
}
```
# Actor output Schema
## `jobs` (type: `string`):
One row per job listing.
# 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 '' with your token
const client = new ApifyClient({
token: '',
});
// Prepare Actor input
const input = {
"queries": [
"software engineer"
],
"location": "New York, United States",
"country": "us"
};
// Run the Actor and wait for it to finish
const run = await client.actor("veeronica/google-jobs-scraper").call(input);
// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`πΎ 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);
});
// π Want to learn more π? Go to β 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 '' with your token.
client = ApifyClient("")
# Prepare the Actor input
run_input = {
"queries": ["software engineer"],
"location": "New York, United States",
"country": "us",
}
# Run the Actor and wait for it to finish
run = client.actor("veeronica/google-jobs-scraper").call(run_input=run_input)
# Fetch and print Actor results from the run's dataset (if there are any)
print("πΎ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
print(item)
# π Want to learn more π? Go to β https://docs.apify.com/api/client/python/docs/quick-start
```
## CLI example
```bash
echo '{
"queries": [
"software engineer"
],
"location": "New York, United States",
"country": "us"
}' |
apify call veeronica/google-jobs-scraper --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=veeronica/google-jobs-scraper",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "β‘ Google Jobs Scraper",
"description": "Scrape Google Jobs listings by keyword and location. Get titles, companies, locations, salaries, posting dates, employment types, descriptions, and every apply link as clean JSON β no login or API key needed.",
"version": "1.0",
"x-build-id": "ZkCTRkmT6n6gUmfZJ"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/veeronica~google-jobs-scraper/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-veeronica-google-jobs-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/veeronica~google-jobs-scraper/runs": {
"post": {
"operationId": "runs-sync-veeronica-google-jobs-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/veeronica~google-jobs-scraper/run-sync": {
"post": {
"operationId": "run-sync-veeronica-google-jobs-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
}
},
"components": {
"schemas": {
"inputSchema": {
"type": "object",
"required": [
"queries"
],
"properties": {
"queries": {
"title": "Search queries",
"type": "array",
"description": "Job titles, skills, or roles to search for β exactly what you'd type into Google's job search box (e.g. software engineer, registered nurse, product manager). Each query is searched on its own.",
"items": {
"type": "string"
}
},
"location": {
"title": "Location",
"type": "string",
"description": "City, region, or country to search in (e.g. New York, London, Remote). Appended to each query as \"β¦ near <location>\". Leave empty to let Google decide from the country."
},
"country": {
"title": "Country",
"enum": [
"us",
"gb",
"ca",
"au",
"ie",
"nz",
"in",
"sg",
"hk",
"ph",
"my",
"id",
"th",
"vn",
"pk",
"jp",
"kr",
"tw",
"br",
"mx",
"ar",
"cl",
"co",
"pe",
"cr",
"ec",
"pa",
"uy",
"ae",
"sa",
"qa",
"kw",
"bh",
"om",
"il",
"eg",
"ma",
"ng",
"za",
"tr"
],
"type": "string",
"description": "Which country/region to search from. Set this to match your Location. Note: Google does not surface job results in some regions, including the EU.",
"default": "us"
},
"language": {
"title": "Language",
"type": "string",
"description": "2-letter language code for the results (e.g. en, fr, es).",
"default": "en"
},
"maxItems": {
"title": "Maximum jobs",
"minimum": 0,
"type": "integer",
"description": "How many job listings to return in total (across all queries). Use 0 for no limit.",
"default": 50
},
"jobType": {
"title": "Employment type",
"enum": [
"fulltime",
"parttime",
"internship",
"contract"
],
"type": "string",
"description": "Restrict results to a single employment type. Leave empty to include all types."
},
"datePosted": {
"title": "Date posted",
"enum": [
"any",
"past24h",
"past3Days",
"pastWeek",
"pastMonth"
],
"type": "string",
"description": "Only return jobs posted within this time window.",
"default": "any"
},
"remote": {
"title": "Remote only",
"type": "boolean",
"description": "Only return remote / work-from-home jobs.",
"default": false
}
}
},
"runsResponseSchema": {
"type": "object",
"properties": {
"data": {
"type": "object",
"properties": {
"id": {
"type": "string"
},
"actId": {
"type": "string"
},
"userId": {
"type": "string"
},
"startedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"finishedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"status": {
"type": "string",
"example": "READY"
},
"meta": {
"type": "object",
"properties": {
"origin": {
"type": "string",
"example": "API"
},
"userAgent": {
"type": "string"
}
}
},
"stats": {
"type": "object",
"properties": {
"inputBodyLen": {
"type": "integer",
"example": 2000
},
"rebootCount": {
"type": "integer",
"example": 0
},
"restartCount": {
"type": "integer",
"example": 0
},
"resurrectCount": {
"type": "integer",
"example": 0
},
"computeUnits": {
"type": "integer",
"example": 0
}
}
},
"options": {
"type": "object",
"properties": {
"build": {
"type": "string",
"example": "latest"
},
"timeoutSecs": {
"type": "integer",
"example": 300
},
"memoryMbytes": {
"type": "integer",
"example": 1024
},
"diskMbytes": {
"type": "integer",
"example": 2048
}
}
},
"buildId": {
"type": "string"
},
"defaultKeyValueStoreId": {
"type": "string"
},
"defaultDatasetId": {
"type": "string"
},
"defaultRequestQueueId": {
"type": "string"
},
"buildNumber": {
"type": "string",
"example": "1.0.0"
},
"containerUrl": {
"type": "string"
},
"usage": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "integer",
"example": 1
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
},
"usageTotalUsd": {
"type": "number",
"example": 0.00005
},
"usageUsd": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "number",
"example": 0.00005
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
}
}
}
}
}
}
}
}
```