Snagajob.com Jobs Search Scraper: Extract Hourly Job Listings at Scale

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What Is Snagajob.com?

Snagajob is one of the largest U.S. platforms focused on hourly and part-time employment, connecting workers with employers in industries like food service, retail, healthcare, and hospitality. With millions of listings across thousands of ZIP codes, manually collecting this data is impractical. The Snagajob Jobs Search Scraper automates extraction from search result pages, turning paginated listings into clean, structured datasets.

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Overview

The Snagajob Search Scraper targets Snagajob's search results pages and extracts rich job record data for each listing. Designed for:

• Job aggregators building multi-source hourly job boards
• Labor market researchers analyzing wage trends and hiring demand
• Workforce analysts tracking industry-specific job availability by region
• Recruiters benchmarking competitor postings and compensation

Key features include configurable result limits per URL, resilient error handling, and support for paginated search queries.

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Input Format

The scraper accepts a JSON configuration object:

{
  "urls": [
    "https://www.snagajob.com/search?q=restaurant&radius=20&query_trigger=def_static&page=2"
  ],
  "ignore_url_failures": true,
  "max_items_per_url": 50
}

Field	Type	Description
urls	array	One or more Snagajob search result URLs. Supports keyword (q=), radius (radius=), and pagination (page=) parameters. Add URLs one by one or via bulk edit.
max_items_per_url	integer	Maximum records to collect per URL. Default: 20. Increase up to your needs (e.g., 50) to capture more results per page.
ignore_url_failures	boolean	If true, the scraper continues when a URL fails instead of halting the entire run. Recommended for bulk jobs. Default: true.

Tip: To collect jobs across multiple pages, add separate URLs with incremented page= values (e.g., page=1, page=2, page=3).

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Output Format

Sample output

{
  "application_url": "https://www.snagajob.com/api/jobs/v1/1229577401/apply",
  "apply_session_type": "DirectApply",
  "customer_id": "54109640",
  "distance_in_miles": null,
  "is_sponsored": false,
  "is_pixel_enabled": true,
  "job_fit_score": 0.0,
  "job_fit_confidence": 0.0,
  "rank": 31,
  "saj_val": 1.16,
  "saj_val_billable": true,
  "score": 0.53739,
  "suppression_level": 0,
  "fextures": [
    "housekeeping",
    "restaurantoperations",
    "dishwashing",
    "restaurantrelated",
    "cleaning",
    "communicationskills",
    "hirevets",
    "flexiblehours",
    "foodservicerelated"
  ],
  "normalized_brand_name": "SSP",
  "normalized_job_title": "Dishwasher",
  "my_property": 0,
  "update_date": "2026-05-17T04:55:24+00:00",
  "onet_code": "35-9021.00",
  "is_brand_title_stacked": true,
  "stacked_job_count": 2,
  "posting_id": "1229577401",
  "company_name": "SSP",
  "title": "Restaurant Dishwasher",
  "logo_url": "https://media.snagajob.com/ui/app/icons/other.png",
  "logo_media_id": "d9c25d52221c4abda3dabc9fbc87f8ca",
  "categories": [
    "Full-time",
    "Part-time"
  ],
  "features": null,
  "industries": [],
  "is_expired": false,
  "is_contractor": false,
  "is_honeypot": false,
  "is_one_click": false,
  "is_easy_apply": false,
  "created_date": "2026-02-10T22:08:36.938Z",
  "location": {
    "location_id": "0",
    "location_name": "Madison, WI, United States",
    "address_line1": null,
    "address_line2": null,
    "city": "Madison",
    "state_province": "Wisconsin",
    "state_province_code": "WI",
    "postal_code": "53718"
  },
  "wages": {
    "text": "$18.00 per hour",
    "short_form_text": "$18.00",
    "wage_type": 1,
    "wage_source": 1,
    "min": null,
    "median": 18.0,
    "max": null,
    "wage_quality": "excellent"
  },
  "wage": {},
  "estimated_wage": {
    "median": 13.34
  },
  "experience_level": 1,
  "posting_type": "FeedThirdParty"
}

Each job listing returns a structured record with 40+ fields:

Identification & Ranking

Field	Meaning
Posting ID	Unique internal identifier for the job posting
Customer ID	Employer/advertiser account identifier
Rank	Position of the listing in search results
Score	Internal relevance score assigned by Snagajob's search engine
Job Fit Score	Estimated match score between the listing and a candidate profile
Job Fit Confidence	Confidence level of the fit score calculation
SAJ Val	Snagajob internal valuation metric for the listing
SAJ Val Billable	Whether the listing's value is counted as billable
Suppression Level	Flag indicating if/how the listing is suppressed in results
ONET Code	Occupational classification code (O*NET standard)

Job Details

Field	Meaning
Title	Job title as displayed in the listing
Normalized Job Title	Standardized/cleaned version of the job title
Company Name	Name of the hiring employer
Normalized Brand Name	Standardized employer brand name
Location	City, state, and/or ZIP of the job
Distance In Miles	Distance from the search query location
Experience Level	Required experience (e.g., entry-level, mid-level)
Posting Type	Type of posting (e.g., organic, sponsored)
Categories	Job categories assigned to the listing
Industries	Industry tags (e.g., Food & Beverage, Retail)

Compensation

Field	Meaning
Wages	Raw wage data object (may include range details)
Wage	Primary wage value displayed on the listing
Estimated Wage	Snagajob-estimated compensation when not explicitly stated

Listing Flags & Features

Field	Meaning
Is Sponsored	Whether the listing is a paid/sponsored placement
Is Pixel Enabled	Whether tracking pixel is active for the listing
Is Expired	Whether the listing is no longer active
Is Contractor	Whether the role is a contractor position
Is Honeypot	Internal fraud/quality detection flag
Is One Click	Whether one-click apply is available
Is Easy Apply	Whether simplified application flow is enabled
Is Brand Title Stacked	Whether the employer brand and title are displayed stacked
Stacked Job Count	Number of similar jobs grouped under a stacked brand listing
Features	Special listing features (e.g., urgently hiring, flexible schedule)
Fextures	Additional internal feature flags
My Property	Internal property classification field

Application & Media

Field	Meaning
Application URL	Direct link to apply for the job
Apply Session Type	Application flow type (e.g., native, redirect)
Logo URL	URL to the employer's logo image
Logo Media ID	Internal media ID for the employer logo

Dates

Field	Meaning
Created Date	When the listing was first published
Update Date	Last modification timestamp

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How to Use

1. Build your search URL — Go to Snagajob.com, run a search with your desired keywords, radius, and filters, then copy the URL from your browser.
2. Add pagination — Append &page=2, &page=3, etc. as separate entries in the urls array for broader coverage.
3. Set item limit — Use max_items_per_url to control how many results to collect per page (up to the page's available listings).
4. Enable fault tolerance — Keep ignore_url_failures: true to prevent single failed pages from stopping bulk runs.
5. Export — Download results as JSON, CSV, or Excel for use in BI tools, databases, or spreadsheets.

Common issues:

• If results are empty, verify the URL returns listings in a browser — some filter combinations may yield zero results.
• Snagajob search URLs may include session tokens; use clean, reproducible URLs without temporary parameters.

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Use Cases & Business Value

• Wage benchmarking: Collect wage data across regions to compare hourly pay rates by industry
• Demand mapping: Identify which cities or ZIP codes have the highest hourly job density
• Job board aggregation: Feed Snagajob data into a custom listing platform
• Sponsorship analysis: Use Is Sponsored and SAJ Val Billable fields to study paid placement patterns in hourly job markets

The scraper eliminates manual browsing across hundreds of paginated search pages, delivering consistent data that scales from tens to thousands of records per run.

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Conclusion

The Snagajob.com Jobs Search Scraper is purpose-built for anyone who needs hourly job market data at scale. With 40+ structured fields covering wages, location, application methods, and listing metadata, it provides everything needed for research, aggregation, or competitive analysis. Configure a search URL, set your limits, and start extracting in minutes.