🚀 Apify Google Jobs Scraper

The most efficient, reliable, and developer-friendly Google Jobs scraper for Apify platform

This Actor uses price per results billing model. We also have a price per event billing model that operates the same way. If you prefer price-per-event billing, please see our Google Jobs Scraper - Price Per Event actor here.

🌟 Why Choose This Scraper?

The Google Jobs data scraper delivers enterprise-grade performance with these advanced capabilities:

Performance & Reliability: Built with modern Python async/await patterns and optimized for high-throughput scraping with intelligent rate limiting.

Cost-Effective: Provides for consistent, reliable results without the overhead of browser automation, cookies, or other rental costs.

Lightning-Fast Search & Retrieval: Search any keyword or job title across Google Jobs with blazing-fast performance. Retrieve comprehensive results in seconds, not minutes, with intelligent caching and optimization.

Precision Targeting & Advanced Filtering: Pinpoint exact locations with radius-based searches, filter by country and language, and apply sophisticated targeting parameters. Get precisely the job data you need, when you need it.

Rich, Structured Data Extraction: Extract complete job information, including application links, and comprehensive job descriptions. Our advanced parsing ensures you get clean, structured data ready for immediate use.

Enterprise-Grade Configuration & Flexibility: Built for developers and businesses who demand reliability. Highly configurable with intuitive controls, comprehensive error handling, and robust logging. Focus on your business logic while we handle the complexity of job scraping.

No Hidden Costs or Rental Fees: We do not charge monthly rentals, our scraper operates on a pay-per-result model. Scale up or down based on your actual needs without being locked into expensive subscriptions.

💰 Billing Model

This Actor uses a Pay-Per-Result (PPR) billing model. You are charged based on the number of job results produced and stored in the dataset.

Controlling Costs

To limit the maximum number of results and control costs, you can set the ACTOR_MAX_PAID_DATASET_ITEMS environment variable. For example:

• Setting ACTOR_MAX_PAID_DATASET_ITEMS=1000 will cap results at 1,000, resulting in a maximum charge of $15.00
• Setting ACTOR_MAX_PAID_DATASET_ITEMS=500 will cap results at 500, resulting in a maximum charge of $7.50

The Actor will automatically check your available funds before starting and will stop gracefully if insufficient funds are available.

What Counts as a Result?

Each job listing that is successfully pushed to the dataset counts as one result. This includes:

• Individual job postings with complete metadata
• Each job record with search parameters, timestamps, and job details

🚀 Features

Core Capabilities

• Advanced Search: Support for complex queries with location, country, and language filtering
• Intelligent Pagination: Automatic handling of Google Jobs pagination with configurable limits
• Location Targeting: Precise location-based searches with radius support
• Multi-Language: Support for international job markets

Data Quality

• Clean Output: Automatic structured data metadata for clean, production-ready data
• Structured Results: Consistent JSON structure across all job listings
• Comprehensive Fields: Job title, company, location, description, salary, and more
• Metadata Tracking: Page-level analytics and search performance metrics

📖 Usage Examples

Basic Job Search Example

Search for a programmer job in San Francisco, CA.

{
  "query": "Software Engineer",
  "location": "San Francisco, CA"
}

Advanced Job Search Example

Search for a job in San Francisco, CA, with a radius of 25 miles, and return 1,000 results. Limit to 10 pages.

{
  "query": "Software Engineer",
  "location": "San Francisco, CA",
  "country": "us",
  "language": "en",
  "google_domain": "google.com",
  "num_results": 1000,
  "max_pagination": 10,
  "include_lrad": false,
  "lrad_value": "25"
}

🔍 Input References

Input Parameters

Parameter	Type	Required	Default	Description
query	str	✅	-	Job search query
location	Optional[str]	❌	None	Job location (city, state, country)
country	str	❌	"us"	Country code for search
language	str	❌	"en"	Language code
google_domain	str	❌	"google.com"	Google domain to use
num_results	int	❌	100	Maximum results to return
max_pagination	Optional[int]	❌	None	Maximum pages to fetch
include_lrad	bool	❌	False	Include location radius
lrad_value	Optional[str]	❌	None	Location radius value

📊 Output Format

Job Listing Structure

{
  "total_jobs_found": 150,
  "pages_processed": 15,
  "search_metadata": {
    "query": "Software Engineer",
    "location": "San Francisco, CA",
    "country": "us",
    "language": "en"
  },
  "jobs": [
    {
      "title": "Senior Software Engineer",
      "company_name": "Tech Corp",
      "location": "San Francisco, CA",
      "description": "We're looking for a senior engineer...",
      "salary": "$150,000 - $200,000",
      "job_type": "Full-time",
      "posted_date": "2 days ago",
      "application_link": "https://company.com/careers/123",
      "company_logo": "https://logo.url",
      "requirements": [
        "5+ years Python experience",
        "Experience with cloud platforms",
        "Strong communication skills"
      ]
    }
  ]
}

Made with ❤️

Transform your job search automation with the most reliable and efficient Google Jobs scraper on the market. Last Updated: 2025.11.14