Foundit Jobs Scraper

Extract comprehensive job data from Foundit.in with ease. Collect job listings including titles, companies, locations, salaries, and descriptions at scale. Perfect for job market research, recruitment, and career analysis.

Features

• Comprehensive Job Data — Extract titles, companies, salaries, and full descriptions
• Flexible Search — Search by keyword, location, or custom URLs
• Automatic Pagination — Collect thousands of jobs across multiple pages
• Fast and Reliable — API-based extraction for consistent results

Use Cases

Job Market Research

Analyze current job trends and salary ranges across industries. Understand demand for specific skills and locations to make informed career decisions.

Recruitment Intelligence

Find qualified candidates by monitoring new job postings. Track competitor hiring patterns and requirements to build better talent strategies.

Career Planning

Research job opportunities and requirements in your field. Compare salaries and benefits across companies to negotiate better offers.

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Input Parameters

Parameter	Type	Required	Default	Description
url	String	No	https://www.foundit.in/search/software-engineer-jobs-in-bangalore	Foundit search URL to derive filters from
keyword	String	No	software engineer	Job search keyword(s)
location	String	No	Bangalore	Job location filter
results_wanted	Integer	No	20	Max jobs to collect
max_pages	Integer	No	20	Max API pages to visit
proxyConfiguration	Object	No	-	Optional Apify proxy settings

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Output Data

Each item in the dataset contains:

Field	Type	Description
source	String	Data source identifier
api_source	String	API endpoint used
url	String	Job listing URL
apply_url	String	Direct application URL
title	String	Job title
company	String	Company name
location	String	Job location
salary	String	Salary information
experience	String	Required experience
skills	Array	Required skills
employment_type	String	Full-time, part-time, etc.
industry	String	Industry category
function	String	Job function
occupational_category	String	Occupational category
description_html	String	HTML job description
description_text	String	Plain text job description
date_posted	String	Posting date
valid_through	String	Application deadline
job_id	String	Unique job identifier
page_no	Number	Page number where found
keyword	String	Search keyword used
input_location	String	Location filter used
scraped_at	String	Timestamp of scraping

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Usage Examples

Basic Job Search

Extract jobs by keyword and location:

{
  "keyword": "software engineer",
  "location": "Bangalore",
  "results_wanted": 50
}

Advanced Filtering

Use a specific search URL for precise results:

{
  "url": "https://www.foundit.in/search/data-scientist-jobs-in-mumbai",
  "results_wanted": 100,
  "max_pages": 5
}

Large Scale Collection

Collect extensive job data with proxy configuration:

{
  "keyword": "marketing manager",
  "location": "Delhi",
  "results_wanted": 500,
  "max_pages": 50,
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": ["RESIDENTIAL"]
  }
}

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Sample Output

{
  "source": "foundit",
  "api_source": "searchResultsPage",
  "url": "https://www.foundit.in/job/software-engineer-12345",
  "apply_url": "https://www.foundit.in/apply/12345",
  "title": "Senior Software Engineer",
  "company": "Tech Solutions Pvt Ltd",
  "location": "Bangalore, Karnataka",
  "salary": "₹8,00,000 - ₹15,00,000 P.A.",
  "experience": "3-5 years",
  "skills": ["Java", "Spring Boot", "Microservices"],
  "employment_type": "Full Time",
  "industry": "IT Services",
  "function": "Engineering",
  "occupational_category": "Software Development",
  "description_html": "<p>Join our dynamic team...</p>",
  "description_text": "Join our dynamic team as a Senior Software Engineer...",
  "date_posted": "2024-01-15",
  "valid_through": "2024-02-15",
  "job_id": "12345",
  "page_no": 1,
  "keyword": "software engineer",
  "input_location": "Bangalore",
  "scraped_at": "2024-01-15T10:30:00Z"
}

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Tips for Best Results

Choose Effective Keywords

• Use specific job titles (e.g., "data scientist" vs "data")
• Include location in keywords when possible
• Test different keyword variations

Optimize Collection Size

• Start with smaller batches (20-50) for testing
• Increase gradually for production runs
• Balance speed with data requirements

Use Proxy Configuration

• Enable residential proxies for better success rates
• Especially important for large-scale collections
• Reduces blocking and improves reliability

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Integrations

Connect your data with:

• Google Sheets — Export for analysis and reporting
• Airtable — Build searchable job databases
• Slack — Get notifications for new opportunities
• Webhooks — Send data to custom endpoints
• Make — Create automated job monitoring workflows
• Zapier — Trigger actions based on job criteria

Export Formats

Download data in multiple formats:

• JSON — For developers and APIs
• CSV — For spreadsheet analysis
• Excel — For business reporting
• XML — For system integrations

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Frequently Asked Questions

How many jobs can I collect?

You can collect all available jobs matching your criteria. The practical limit depends on the search parameters and website availability.

Can I search for jobs in multiple locations?

Yes, you can run separate searches for different locations or use broader location terms to capture multiple areas.

What if some job fields are empty?

Some fields may be empty if the job posting doesn't include that information. The actor collects all available data.

How often should I run the scraper?

Run frequency depends on your needs. Job postings change regularly, so daily or weekly runs are common for monitoring.

Can I filter by salary or experience?

Use specific keywords in your search or filter results after collection using the output data.

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Support

For issues or feature requests, contact support through the Apify Console.

Resources

• Apify Documentation
• API Reference
• Scheduling Runs

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Legal Notice

This actor is designed for legitimate data collection purposes. Users are responsible for ensuring compliance with website terms of service and applicable laws. Use data responsibly and respect rate limits.