Google Jobs Scraper 🔍

A powerful and efficient Google Jobs Scraper built for the Apify platform. Search for jobs by query, location, and various filters, fetch detailed job information, and estimate salaries for different positions.

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Why use this Google Jobs Scraper? 🚀

• ✅ Comprehensive Job Search: Search jobs with advanced filters (location, date posted, employment type, remote jobs, etc.)
• ✅ Multiple Modes: Job search, job details by ID, and salary estimation
• ✅ Scalable & Reliable: Built-in retry logic, API key rotation, and batch processing
• ✅ Clean JSON Output: Structured data ready for analytics, dashboards, and integrations
• ✅ Best Practices: Follows Apify actor development standards with proper error handling

Target Keywords: Google Jobs Scraper, Job Search, Job Data Extraction, Employment Data Scraper, Salary Estimator, Job Market Analysis

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Table of Contents 📚

• Features
• How it Works
• Quick Start
• Input Configuration
• Example Inputs
• Example Outputs
• SEO Keywords
• Best Practices
• FAQ
• Changelog

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Features ✨

Feature	Description
Job Search	Search jobs by query with filters (location, date, remote, employment type)
Job Details	Fetch detailed information for specific job IDs
Salary Estimation	Estimate salaries for job titles in specific locations
Advanced Filters	Filter by company type, job requirements, categories, radius, and more
Multi-Query Support	Process multiple search queries in a single run
Pagination	Automatically fetch multiple pages of results
Rate Limiting	Configurable delays between requests to avoid API limits

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How it Works 🧠

1. API Integration: Connects to a jobs data provider via HTTPS to access Google Jobs-related data
2. Three Modes:
   • Search Mode: Search for jobs using queries and filters
   • Job Details Mode: Get detailed information for specific job IDs
   • Salary Estimation Mode: Estimate salaries for job titles
3. Batch Processing: Results are batched (100 items) for efficient data storage
4. Data Output: All results are saved to Apify dataset in structured JSON format

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FAQ ❓

• What is a Google Jobs Scraper? A Google Jobs Scraper is a tool that collects job listings and related details from Google’s job search results so you can analyze or use the data in your own workflows.

• How do I scrape job listings from Google? Provide a job query (for example, "software engineer in New York"), set optional filters (location, date posted, remote only), and run the actor. The results are saved to the Apify dataset.

• Is it legal to scrape Google Jobs data? Always review and follow the terms of service of the websites and services you access. Only scrape data you are allowed to collect, and respect robots, rate limits, and local laws.

• What tools can I use to scrape job listings from Google? You can use this Apify actor. It provides input parameters, batching, retries, and dataset exports so you don’t have to build everything from scratch.

• Can I scrape job data using Python? Yes. While this actor runs on Node.js, you can export the dataset (JSON/CSV) and process it in Python, or call the actor via API from your Python scripts.

• What are the challenges in scraping Google job postings? Rate limits, changing HTML/structures, and data quality. This actor helps with retries, delays, and structured outputs to reduce these issues.

• Can I automate the job scraping process? Yes. You can schedule the actor on Apify, pass recurring inputs, and export results automatically to your storage or integrations.

• Are there any free tools for Google job scraping? There are free options with limited quotas. For heavier workloads, consider paid plans or your own infrastructure.

• How do I extract job data from Google Careers? Use the same query and filters in this actor targeting the roles and locations you want. The output includes fields like title, company, location, description, and apply link.

• What is the best Google Jobs scraper for large-scale scraping? The “best” depends on your needs. This actor focuses on reliability (retries, batching), flexibility (filters), and automation (scheduling, exports), which are key for scale.

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Quick Start 🏁

1. Configure Input

Provide the desired inputs (queries, filters, pages) based on the configuration below.

2. Run the Actor

Start the actor and monitor the dataset for results.

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Input Configuration ⚙️

Common Parameters

Parameter	Type	Default	Description
mode	string	search	Mode: search, job-details, or estimate-salary
query	string	-	Single search query (e.g., "software engineer")
queries	array	-	Multiple search queries
country	string	us	Country code (us, uk, ca, in, etc.)
language	string	en	Language code (en, es, fr, etc.)
location	string	-	Specific location (e.g., "New York, NY")
num_pages	integer	1	Number of pages to scrape (max 20)

Search Filters

Parameter	Type	Default	Description
date_posted	string	all	Filter: all, today, 3days, week, month
remote_jobs_only	boolean	false	Show only remote jobs
employment_types	string	-	FULLTIME, CONTRACTOR, PARTTIME, INTERN (comma-sep)
job_requirements	string	-	Experience/degree requirements
employer	string	-	Filter by specific employer
radius	integer	50	Search radius in kilometers
categories	string	-	Job categories (comma-separated)

Job Details Mode

Parameter	Type	Description
job_id	string	Single job ID to fetch details
job_ids	array	Multiple job IDs

Salary Estimation Mode

Parameter	Type	Default	Description
job_title_for_salary	string	-	Single job title for salary estimation
job_titles_for_salary	array	-	Multiple job titles
salary_location	string	United States	Location for salary estimation
salary_radius	integer	100	Search radius in kilometers

Performance Tuning

Parameter	Type	Default	Description
delay_between_pages	number	1	Delay in seconds between pages
delay_between_requests	number	0.5	Delay in seconds between individual requests

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Example Inputs 📥

1) Simple Job Search

{
  "mode": "search",
  "query": "software engineer in San Francisco",
  "country": "us",
  "num_pages": 3
}

2) Advanced Job Search with Filters

{
  "mode": "search",
  "queries": [
    "data scientist",
    "machine learning engineer"
  ],
  "location": "New York, NY",
  "country": "us",
  "date_posted": "week",
  "remote_jobs_only": false,
  "employment_types": "FULLTIME",
  "num_pages": 5,
  "delay_between_pages": 2
}

3) Remote Jobs Only

{
  "mode": "search",
  "query": "frontend developer",
  "country": "us",
  "remote_jobs_only": true,
  "employment_types": "FULLTIME,CONTRACTOR",
  "num_pages": 3
}

4) Get Job Details by ID

{
  "mode": "job-details",
  "job_ids": [
    "yCbVETOW_si5sBKRAAAAAA==",
    "hM2b1Y7Duj5sKiX5AAAAAA=="
  ],
  "delay_between_requests": 1
}

5) Estimate Salaries

{
  "mode": "estimate-salary",
  "job_titles_for_salary": [
    "Software Engineer",
    "Product Manager",
    "Data Scientist"
  ],
  "salary_location": "San Francisco, CA",
  "salary_radius": 50
}

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Example Outputs 📤

Job Search Result

{
  "job_id": "yCbVETOW_si5sBKRAAAAAA==",
  "job_title": "Software Engineer",
  "employer_name": "Tech Company Inc.",
  "employer_logo": "https://example.com/logo.png",
  "job_employment_type": "FULLTIME",
  "job_location": "San Francisco, CA",
  "job_city": "San Francisco",
  "job_state": "California",
  "job_country": "US",
  "job_latitude": 37.7749,
  "job_longitude": -122.4194,
  "job_is_remote": false,
  "job_posted_at_datetime_utc": "2025-10-06T00:00:00.000Z",
  "job_description": "Full job description...",
  "job_apply_link": "https://example.com/apply",
  "job_min_salary": 120000,
  "job_max_salary": 180000,
  "job_salary_period": "YEAR",
  "job_benefits": ["health_insurance", "dental_coverage"],
  "job_highlights": {
    "Qualifications": ["5+ years experience", "Bachelor's degree"],
    "Responsibilities": ["Design and develop software", "Collaborate with team"],
    "Benefits": ["Competitive salary", "Health insurance"]
  },
  "search_query": "software engineer",
  "scraped_at": "2025-10-14T10:00:00.000Z"
}

Summary Result

{
  "_summary": true,
  "success": true,
  "mode": "search",
  "total_jobs_scraped": 150,
  "total_pages": 5,
  "scraped_at": "2025-10-14T10:05:00.000Z"
}

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## Changelog 📦

### Version 1.0.0 (2025-10-14)
- ✨ Initial release
- ✅ Job search with advanced filters
- ✅ Job details by ID
- ✅ Salary estimation
- ✅ Multi-query support
- ✅ Comprehensive error handling

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## SEO Keywords 🔎

Use these relevant keywords to help users discover this actor. They are grouped and de-duplicated for clarity:

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- **APIs & Scripts**: Google Jobs API, Google job scraping API, Job search scraping script, Job posting scraping script, Google Jobs scraping Python code, Scrape job data using Python, Google job listing scraper Python
- **Targets & Sources**: Scrape Google for job listings, Web scraping for jobs, Scraping job search engines, Google Careers scraper, Scrape job data from Google Careers, Web scraping Google job results, Job scraping from Google search results
- **Use-cases & Services**: Google Jobs data extraction, Extract job data from Google, Google job listings automation, Google job scraping service, Google job data mining, Job board scraping from Google
- **Free Options**: Free Google job scraping tools, Google Jobs scraper free

These keywords are suggestions. Pick the ones that fit your exact use case and audience.

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## Support & Contributing 💬

For issues, questions, please contact.

**Happy Job Scraping! 🎉**