Snagajob Scraper — Hourly & Part-Time US Job Listings, Wages & Employer Data

Snagajob Scraper turns Snagajob.com — the largest US job board for hourly work — into structured datasets. In a single run it extracts hourly and part-time job listings across retail, restaurants, warehouses, healthcare support, delivery and more, returning job ID, title, company, city/state, verified hourly wage range, employment type, shift and the direct application URL — plus, optionally, the full description, requirements and benefits. Priced per job ($0.0015/result) with auto-pagination up to 100,000 listings per run, and no browser, captchas or proxies needed. Any data team can add US hourly job market data to a database, dashboard or AI pipeline in minutes.

The Actor runs on the Apify platform, so you get REST API access, scheduling, integrations (Zapier, Make, Google Sheets) and monitoring out of the box.

Main Use Cases

• Staffing & recruiting research — benchmark hourly openings, posted wages and employer demand by keyword, city or ZIP.
• Wage & labor-market analysis — collect structured pay data (wageMin/wageMax/wageUnit/wageVerified) to compare hourly rates across US metros.
• Job databases & job boards — enrich your own product with Snagajob listings, including direct apply URLs.
• Workforce monitoring — track retail, restaurant and warehouse openings per brand over time (weekly scheduled runs).
• AI agents & LLM pipelines — feed a job-search assistant, recommendation engine or market-trend model with clean, deduplicated job objects.

How It Works

Snagajob's website is protected by Cloudflare, which blocks datacenter IPs. However, Snagajob's official JobGet MCP server (https://platform.jobget.com/jobs-mcp/mcp) is public and not IP-blocked, exposing two tools:

• search_jobs — ranked search by location, keyword, radius, employment type, shift and date posted
• get_job_details — full details (description, requirements, benefits, ZIP, coordinates)

The Actor calls this endpoint directly over JSON-RPC (no browser, no DOM parsing, no proxy). Because the search API caps every query at 25 results, the Actor auto-paginates by sweeping filter combinations (employment type × shift × date posted), gathering every variation and de-duplicating by job ID. Details are fetched with a small concurrent worker pool.

Track US Hourly Job Market Trends

Run this Actor weekly per metro or state and you get a time series of hourly openings: how many jobs, which employers, which shifts (day, evening, night, overnight, weekend), and at what posted wages. Combine the datePosted filter (today, last_3_days, last_week, last_30_days) with employmentType (full_time, part_time, seasonal, temporary) to isolate fresh, part-time or seasonal postings for trend analysis.

Build Part-Time Job Databases for Recruitment Research

With ~35 million Americans working part-time hours, Snagajob is the single deepest source of US hourly/part-time postings. Set employmentType: "part_time", add several related keywords (e.g. waiter, bartender, host) and let fillWithOtherJobs top up the rest with every other hourly job near the location — then export the whole dataset as JSON, CSV, Excel or HTML.

Monitor Hourly Wages Across US Cities

Every search result already carries wageMin, wageMax, wageUnit and wageVerified. Enable includeDescription to also get the verified flag and full posting text. Because pay is employer-posted per hour, you can benchmark like-for-like rates — retail vs. warehouse vs. healthcare support — across cities without annual-salary conversions.

Input

Field	Type	Description
keyword	string	Single job keyword (optional). Leave it and keywords empty to scrape all jobs near the location.
keywords	array	Extra keywords; each gets its own full paginated search, merged + de-duplicated (e.g. waiter, bartender).
location	string	City, state or ZIP to search near (e.g. Seattle, WA, 90001, TX).
radius	integer	Search radius in miles (default 20, max 50).
maxItems	integer	Max listings (default 100, max 100,000). The Actor pages through results automatically.
includeDescription	boolean	Fetch full details — description, requirements, benefits, ZIP, coordinates (default true). Add $0.001/job.
fillWithOtherJobs	boolean	Top up keyword results below maxItems with all other nearby hourly jobs (default true).
employmentType	string	Filter: full_time, part_time, seasonal, temporary. Empty = all.
shift	string	Filter: day, evening, night, overnight, weekend. Empty = all.
datePosted	string	Filter: today, last_3_days, last_week, last_30_days. Empty = all.
startUrls	array	Direct Snagajob job URLs to scrape exactly (e.g. https://www.snagajob.com/jobs/1296915295).
proxy	object	Standard Apify proxy config. Not required (endpoint is not IP-blocked), kept for consistency.

Output

Each dataset item is a flat JSON object. Search-level items contain the core identifiers, location, wages, employment details and the application link; enabling includeDescription (or using direct URLs) adds the enrichment fields:

Field	Description
jobId	Snagajob posting ID
title / companyName / logoUrl	Job title, company and logo
city / state	Job location
distanceInMiles	Distance from the search location
wageMin / wageMax / wageUnit	Employer-posted pay range and unit (hour/day/week/month/year)
wageVerified	Pay verified by the employer
employmentType / shift / schedule	Employment and shift details
postedAt / expiresAt	Posting dates
applicationUrl / jobUrl	Apply link and canonical listing URL
easyApplyEligible / urgentlyHiring	Application and hiring flags
description / requirements / benefits	Full posting text (detail fetch)
postalCode / latitude / longitude	Precise location (detail fetch)
detailCity / detailState / companyUrl	Detail-level location and company (where available)

Dataset views: the Actor declares an overview view (jobId, title, companyName, city, state, wageMin, wageMax, wageUnit, employmentType, jobUrl) — output is also downloadable as JSON, CSV, Excel or HTML.

Example Input

{
  "keyword": "waiter",
  "keywords": ["bartender", "host"],
  "location": "Seattle, WA",
  "radius": 20,
  "maxItems": 1000,
  "includeDescription": true,
  "employmentType": "part_time",
  "datePosted": "last_week"
}

Example Output

{
    "jobId": "1296915295",
    "title": "Dining Room Server",
    "companyName": "Quail Park",
    "city": "Seattle",
    "state": "WA",
    "distanceInMiles": 3.6,
    "wageMin": 17.13,
    "wageMax": 17.5,
    "wageUnit": "hour",
    "wageVerified": true,
    "employmentType": "full_time",
    "shift": null,
    "postedAt": "2026-09-17T08:02:01.508Z",
    "applicationUrl": "https://www.snagajob.com/jobs/1296915295",
    "easyApplyEligible": false,
    "urgentlyHiring": false,
    "jobUrl": "https://www.snagajob.com/jobs/1296915295",
    "description": "Dining Room Server\nQuail Park of Lynnwood\n\nHave you always wanted a fun and rewarding job?...",
    "requirements": ["Strong commitment to customer service", "..."],
    "benefits": ["Medical, Dental and Vision Insurance", "..."],
    "postalCode": "98185",
    "latitude": 47.6602,
    "longitude": -122.3143
}

Integrations & Scheduling

• API: call via POST /v2/acts/ahmed_jasarevic~snagajob-scraper/runs and fetch results from the returned dataset.
• Scheduling: schedule a run weekly (or daily) to monitor hourly job market changes — openings, wages and new employers per market.
• Automation: Zapier, Make (Integromat), Google Sheets, Slack/email notifications via Apify webhooks.
• Export: dataset output as JSON, CSV, Excel or HTML.

Related Actors

• LinkedIn Jobs Scraper — most-used job scraping Actor on the Apify Store.
• Indeed Scraper — official Apify scraper for the largest job board.
• CareerBuilder Scraper — US salary & listings data (CareerBuilder).
• Jora Job Scraper — Jora (AU/NZ) jobs with salary data.
• eFinancialCareers Scraper — finance job salaries across 23 countries.

FAQ

Does Snagajob have an official public API for job data? No public "pull" API for buyers. Snagajob publishes a partner/employer API (docs.snagajob.com, keyed via X-SAJ-ApiKey) for pushing postings and routing applications — not for pulling listings out. The practical route to hourly job data is collecting the public postings (directly, or via the public JobGet MCP endpoint this Actor uses).

What alternative job data sources exist? For US hourly/entry-level jobs: Indeed, CareerBuilder, ZipRecruiter and LinkedIn Jobs scrapers on the Apify Store; for other regions, Jora (AU/NZ), eFinancialCareers, SEEK and Naukri. Aggregator job-data APIs (e.g. Jobo Data, Hirebase, Coresignal, Bright Data) also sell cleaned feeds but are far more expensive per record than pay-per-result scraping.

What's in each row? See the Output section: every row has the job ID, title, company, city/state, wages (min/max/unit/verified), employment type, dates, application URL and flags; with includeDescription you also get description, requirements, benefits, ZIP and coordinates.

Can I scrape by state/city/ZIP? Yes — pass a city (Seattle, WA), a ZIP (90001) or a state (TX, FL, CA) as location. For state-level sweeps set maxItems high and keyword empty.

How many jobs can I get in one run? Up to 100,000 listings per run (maxItems, default 100). The auto-pagination sweeps filter buckets until all reachable matches are collected or the cap is hit.

What does it cost? Pay-per-result, transparent billing: $0.0015 per search-level job, +$0.001 per job when includeDescription: true (or for direct-URL jobs), plus a one-time $0.00005 actor-start charge. 1,000 listings with descriptions ≈ $2.50. Free Apify accounts get a capped preview (10 items).

Is scraping Snagajob legal? Scraping publicly available job listings is generally acceptable, but you should review Snagajob's Terms of Service and robots.txt, and comply with applicable laws. This Actor is not affiliated with or endorsed by Snagajob or JobGet.

SEO Keywords

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For AI Agents & LLM Apps

Purpose: this Actor is a drop-in tool for agents that need structured US hourly/part-time job data — answering wage questions, building job databases, monitoring hiring trends, or routing users to real postings.

Minimal input: keyword + location (+ optional maxItems, employmentType, datePosted, startUrls). That's all an LLM needs to start a run.

Output fields: jobId, title, companyName, city, state, distanceInMiles, wageMin, wageMax, wageUnit, wageVerified, employmentType, shift, postedAt, applicationUrl, easyApplyEligible, urgentlyHiring, jobUrl; with includeDescription: true also description, requirements, benefits, postalCode, latitude, longitude.

Agent behaviors to keep costs low:

• Set includeDescription: false (default) unless the task genuinely needs full posting text — details add $0.001 per job and increase run cost.
• Keep fillWithOtherJobs off when you only want keyword-matched results.
• Use maxItems to bound the run; pay-per-result means every returned job is billed.

Billing: $0.0015 per result + $0.001 per job with full details (includeDescription) + $0.00005 per run start. ~1,000 jobs with descriptions ≈ $2.50.

Legal & Compliance Disclaimer

This Actor is not affiliated with, endorsed by, or sponsored by Snagajob, JobGet, or any related entity. It collects publicly visible job postings; the user is solely responsible for reviewing Snagajob's Terms of Service and robots.txt and for complying with all applicable laws before using the data. The output contains job posting data only — no job-seeker or applicant profiles are collected. Job descriptions may incidentally include employer contact details (e.g. a business email or phone typed by the employer): use such data only for legitimate, lawful purposes (e.g. job applications, sanctioned outreach) and never for unsolicited marketing. If you encounter any personal data of identifiable individuals, handle it in accordance with applicable privacy laws (e.g. GDPR/CCPA) and only with a valid legal basis.

Use responsibly, respect the operators' terms, and do not overload the source.