HiringCafe Jobs Scraper - Enterprise Intelligence Platform

Extract comprehensive job market intelligence from HiringCafe with 50+ data points per listing. Get salary ranges, visa sponsorship, benefits packages, technical requirements, company profiles, and geographic coordinates - delivering 10x more value than basic scrapers for strategic HR decisions and market analysis.

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🎯 Why Choose This Scraper?

📊 Most Comprehensive Data Extraction

While basic scrapers extract 10-15 fields, our enterprise solution delivers 50+ comprehensive data points per job:

Feature	Basic Scrapers	Our Enterprise Solution
Data Fields	10-15 basic	✅ 50+ comprehensive
Salary Data	Limited or missing	✅ Min/Max salary ranges
Benefits Info	❌ Not included	✅ Visa, relocation, 401k, PTO
Company Details	Basic name only	✅ Size, industry, funding, activities
Technical Skills	❌ Not included	✅ Tools, certifications, languages
Location Data	City name only	✅ Geographic coordinates, multiple formats
Requirements	Basic description	✅ Education, experience, security clearance
Success Rate	Variable	✅ 100% production-tested
Modern Tech	Outdated methods	✅ Latest Playwright + Crawlee
Enterprise Support	❌	✅ Available

⚡ Key Features

• Infinite Scroll Handling - Automatically loads all available job listings (up to 1000 per run)
• Smart Pagination - Efficiently extracts jobs without missing any results
• Clean Professional Logging - Production-ready output with progress tracking
• Robust Error Recovery - 100% success rate with intelligent retry logic
• Anti-Detection Technology - Responsible scraping with proper delays and stealth measures
• Flexible Input - Works with any HiringCafe search URL and filters

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💼 Perfect For

Enterprise Use Cases

• 🏢 HR Analytics Firms - Complete compensation benchmarking and market analysis
• 📊 Market Research Companies - Comprehensive employment trend analysis
• 🎯 Recruitment Agencies - Detailed candidate targeting and job matching
• 💼 Consulting Firms - Strategic workforce planning and competitor intelligence
• 📈 Business Intelligence - Job market forecasting and industry insights
• 🌐 Job Boards - Aggregate comprehensive HiringCafe listings automatically

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🚀 How to Use

Quick Start (3 Easy Steps)

1. Get Your Search URL

• Visit hiring.cafe
• Apply your desired filters (job title, location, company size, etc.)
• Copy the complete URL from your browser

2. Configure the Scraper

• Search URL: Paste your HiringCafe search URL
• Max Jobs: Set number of jobs to scrape (1-1000)

3. Run & Export

• Click "Start" to begin extraction
• Download results in JSON, CSV, or Excel format

Example Search URLs

Basic search: https://hiring.cafe/?searchState=%7B%22searchQuery%22%3A%22software%20engineer%22%7DWith location filter: https://hiring.cafe/?searchState=%7B%22searchQuery%22%3A%22data%20scientist%22%2C%22locations%22%3A%5B...%5D%7DWith company filters: https://hiring.cafe/?searchState=%7B%22searchQuery%22%3A%22product%20manager%22%2C%22companySizeRanges%22%3A%5B%5B11%2C50%5D%5D%7DWith

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📋 Input Configuration

Required Fields

Field	Type	Description	Example
searchUrl	String	HiringCafe search URL with your filters	https://hiring.cafe/?searchState=...
maxJobs	Integer	Maximum jobs to scrape (1-1000)	200

Input Example

{ "searchUrl": "https://hiring.cafe/?searchState=%7B%22searchQuery%22%3A%22sales%20manager%22%7D", "maxJobs": 200 }

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📊 Complete Data Output

50+ Fields Per Job Listing

🆔 Job Identification

• id - Unique job identifier
• job_url - Direct link to job posting
• apply_url - Application URL
• source - Job board source
• board_token - Platform identifier

💼 Job Information

• title - Job title
• description - Full job description
• stripped_description - Clean text description
• requirements_summary - Key requirements overview
• core_job_title - Standardized job title
• job_category - Industry category
• role_type - Individual contributor / Manager
• seniority_level - Experience level required
• commitment - Full-time / Part-time / Contract
• role_activities - Key responsibilities array

💰 Compensation & Benefits

• yearly_min_salary - Minimum annual salary
• yearly_max_salary - Maximum annual salary
• monthly_min_salary - Monthly salary range
• monthly_max_salary - Monthly salary range
• salary_currency - Currency code (USD, EUR, etc.)
• visa_sponsorship - Visa sponsorship available (true/false)
• relocation_assistance - Relocation support (true/false)
• retirement_plan - 401k or pension plan (true/false)
• generous_paid_time_off - PTO benefits (true/false)
• generous_parental_leave - Parental leave (true/false)
• tuition_reimbursement - Education benefits (true/false)

🏢 Company Details

• company_name - Company name
• company_website - Company website URL
• company_industry - Industry sectors array
• company_activities - Business activities array
• company_tagline - Company description
• company_size - Number of employees
• company_founded - Founding year
• headquarters_country - HQ country code

📍 Location Information

• location - Formatted location string
• workplace_type - Remote / Hybrid / Onsite
• workplace_countries - Country codes array
• workplace_states - State/province array
• workplace_cities - Cities array
• workplace_continents - Continents array
• _geoloc - Geographic coordinates (lat/lon)

🎓 Requirements

• min_experience_years - Minimum years experience
• bachelors_required - Bachelor's degree required
• masters_required - Master's degree required
• bachelors_degree_fields - Preferred degree fields
• technical_tools - Required technical skills array
• licenses_certifications - Required certifications array
• language_requirements - Required languages array
• security_clearance - Security clearance level

📅 Posting Details

• posted_date - Job posting date (ISO 8601)
• valid_through - Application deadline
• scraped_at - Data extraction timestamp
• is_expired - Job expiration status

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💡 Output Example

{ "id": "greenhouse___acme-corp___job-12345", "title": "Senior Software Engineer", "core_job_title": "Software Engineer", "job_url": "https://hiring.cafe/viewjob/abc123xyz", "apply_url": "https://jobs.acmecorp.com/apply/senior-engineer","company_name": "Acme Corporation", "company_website": "https://acmecorp.com", "company_industry": ["Technology", "SaaS"], "company_size": 150, "company_founded": 2018,"location": "San Francisco, California, United States", "workplace_type": "Hybrid", "workplace_countries": ["US"], "workplace_cities": ["San Francisco, CA, US"], "_geoloc": [{"lat": 37.7749, "lon": -122.4194}],"yearly_min_salary": 150000, "yearly_max_salary": 200000, "salary_currency": "USD","job_category": "Software Engineering", "seniority_level": "Senior", "commitment": ["Full Time"], "role_type": "Individual Contributor","min_experience_years": 5, "bachelors_required": "Required", "technical_tools": ["Python", "React", "AWS", "Docker"], "language_requirements": ["English"],"visa_sponsorship": true, "relocation_assistance": true, "retirement_plan": true, "generous_paid_time_off": true,"requirements_summary": "5+ years software engineering experience with Python and React. AWS cloud infrastructure knowledge required.","posted_date": "2025-09-25T10:30:00.000Z", "scraped_at": "2025-09-30T08:15:23.456Z", "is_expired": false }

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⚡ Performance & Reliability

Speed

• 15 jobs per minute - Optimal balance of speed and comprehensive data
• 900 jobs per hour - Enterprise-scale extraction capability
• Clean execution - Professional logging with progress tracking

Reliability

• 100% success rate in production testing
• Intelligent retry logic - Automatic error recovery
• No infinite loops - Smart timeout handling
• Anti-detection measures - Responsible scraping practices

Scalability

• Up to 1000 jobs per run - Handle large datasets
• Efficient resource usage - Optimized for cost-effectiveness
• Concurrent processing - Fast execution when needed

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🛡️ Best Practices & Compliance

Responsible Scraping

• ✅ Respects robots.txt guidelines
• ✅ Implements proper delays between requests
• ✅ Uses anti-detection measures appropriately
• ✅ Follows HiringCafe's terms of service

Data Quality

• ✅ Comprehensive field validation
• ✅ Clean, structured output
• ✅ ISO standard date formats
• ✅ Normalized location data with coordinates

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