Hiring.Cafe Jobs Scraper — Structured Job Data with Salary & Company Info

Turn any hiring.cafe search into clean, structured job data — salary, seniority, skills, benefits and enriched company profiles — in seconds, at scale.

Hiring.Cafe aggregates live job postings from thousands of company career pages and ATS platforms — a single search can surface 250,000+ live listings. This scraper turns any hiring.cafe search into a rich, typed dataset: job title, company, location, salary band, seniority, commitment, required skills and languages, benefits, and full descriptions, plus an enriched company profile (HQ country, size, year founded, industries, stock symbol). Search by keyword and location, apply the site's own filters, paste a hiring.cafe search URL, or point it at a single company's page — then export to JSON, CSV, Excel or the API, no code required.

You pay only for the results you keep — no proxy required, and incremental mode bills only what changed (see below).

Why this scraper

• ⚡ Fast & low-cost — a lean, direct data path with no heavy browser, so large runs stay cheap.
• 🧾 Rich, typed records — 90+ structured fields per job, not raw HTML.
• ♻️ Cheap to monitor — incremental mode re-scrapes only what changed (see below).
• 🔔 Notifications built in — Telegram, Slack, Discord or any webhook.
• 🤖 AI- & API-ready — compact output, MCP-friendly, one-click integrations.

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✨ Key features

• 🔎 Search, URL or company scraping — run a keyword + location + filter search, paste hiring.cafe search URLs (filters and all), or drop a company's hiring.cafe page to pull every open role at that employer.
• 🧾 Deeply structured records — normalized salary (min/max/currency/period), seniority, workplace type, job category, required skills, languages, degree requirements and benefit flags.
• 🏢 Enriched company data — website, sector, HQ country, employee count, year founded, industries, organization type and stock symbol.
• 🎚️ Rich filters — workplace type, commitment, seniority, company, "posted within N days" and sort order, all applied on the site.
• 🧠 Full descriptions & contacts — fetch each job's complete description as text, HTML and Markdown, with emails/phones auto-extracted.
• ♻️ Incremental monitoring — schedule it and get only what changed (NEW / UPDATED / EXPIRED); unchanged jobs are skipped before their description is even fetched.
• 🔔 Notifications — Telegram, Slack, Discord or any webhook (n8n / Make / Zapier).
• 🤖 AI-ready — compact and drop-empty output modes keep payloads small for LLMs and MCP.

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📤 Example output

{
  "id": "dayforce___stretto___strettocareers___152",
  "title": "Software Engineer",
  "company": "Stretto",
  "companyWebsite": "stretto.com",
  "location": "United States or Irvine",
  "workplaceType": "Remote",
  "seniorityLevel": "Mid Level",
  "commitment": ["Full Time"],
  "jobCategory": "Software Development",
  "salaryMin": 110000,
  "salaryMax": 130000,
  "salaryCurrency": "USD",
  "salaryPeriod": "Yearly",
  "salaryRange": "USD 110,000 - USD 130,000 (Yearly)",
  "isCompensationTransparent": true,
  "technicalTools": ["Java", "Spring", "Node.js", "ReactJS", "AWS", "SQL", "Python"],
  "languageRequirements": ["English"],
  "requirementsSummary": "5+ years software development; Bachelor's degree in CS; strong backend and frontend skills; AWS, SQL and CI/CD.",
  "visaSponsorship": false,
  "companyHqCountry": "US",
  "companyYearFounded": 1986,
  "companyIndustries": ["Legal Tech", "Financial Services"],
  "postedDate": "2026-05-14T07:00:00.000Z",
  "applyUrl": "https://jobs.dayforcehcm.com/en-US/stretto/strettocareers/jobs/152",
  "source": "hiring.cafe",
  "description": "Full job description as text, HTML and Markdown…"
}

Descriptions are returned as plain text, HTML and Markdown — pick one or all three.

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📚 What data can you extract?

• Core — id, title, company, location, workplace type, seniority, commitment, job category, apply URL and source ATS.
• Compensation — salary min/max, currency, period, formatted range and a transparency flag.
• Requirements — skills/tools, languages, degree requirements by level, licenses/certifications, security clearance, years of experience.
• Benefits & attributes — remote/visa/relocation/retirement/PTO/parental-leave flags, shift & travel needs, physical/cognitive demand.
• Company — website, sector, HQ country, employee count, year founded, industries, organization type, stock exchange & symbol.
• Details (with includeDetails) — full description (text / HTML / Markdown) and auto-extracted contact emails & phones.
• Monitoring — changeType, repost detection, scrapedAt, content hash.

Every field is present in standard mode (missing values are null); compact mode returns the core fields only, for lean AI/MCP payloads.

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⚙️ Input

Configure it in the visual editor — no code needed — or pass JSON via the API.

Field	What it does
query	Keyword search, e.g. "registered nurse" (comma-separate for multiple searches).
location	City, region or country to search near, e.g. "London", "New York".
startUrls	Paste hiring.cafe search URLs (every filter preserved) or a company's page to pull all its open roles.
workplaceTypes	Remote, Hybrid, Onsite, Field.
commitmentTypes	Full Time, Part Time, Contract, Internship, Temporary, Seasonal, Volunteer.
seniorityLevel	No Prior Experience Required, Entry, Mid, Senior.
dateFetchedPastNDays	Only jobs added in the last N days.
includeDetails	Fetch each job's full description and contacts.
incrementalMode	Emit only what changed since the last run.
maxResults	Cap the number of jobs (0 = unlimited).

…and 31 inputs in total — the table shows the essentials; the rest cover sorting, company & advanced search-state filters, output/AI modes, notification channels and tuning, all in the visual editor.

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📥 Example inputs

Copy any of these into the JSON editor, or set the same fields in the visual editor.

1. Simple keyword + location search — grab the 200 newest nursing roles near New York.

{ "query": "registered nurse", "location": "New York", "maxResults": 200 }

2. Filtered search with full descriptions — senior, remote Python roles, each with its complete description and contacts.

{ "query": "python developer", "workplaceTypes": ["Remote"], "seniorityLevel": ["Senior Level"], "includeDetails": true }

3. Every open job at one company — paste a company's hiring.cafe page to pull all its roles, enriched.

{ "startUrls": [{ "url": "https://hiring.cafe/org/stripe" }], "includeDetails": true }

4. Paste a search URL — reuse a hiring.cafe search you built in the browser, filters and all.

{ "startUrls": [{ "url": "https://hiringcafe.com/?searchState=%7B%22searchQuery%22%3A%22data+engineer%22%7D" }] }

5. Scheduled monitoring with alerts — watch a search daily and get only new/changed jobs pushed to Telegram.

{ "query": "product manager", "location": "London", "incrementalMode": true, "telegramToken": "…", "telegramChatId": "@mychannel" }

6. Lean output for AI/MCP — core fields only, empties dropped, for small LLM payloads.

{ "query": "solutions architect", "compact": true, "excludeEmptyFields": true }

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💡 Use cases

• Recruiting & sourcing — build a live, structured feed of open roles by title, location and seniority.
• Labor-market & salary research — analyze compensation, skills demand and hiring trends across companies and industries.
• Company & competitor monitoring — paste a company's hiring.cafe page to pull every open role, enriched with size, sector and HQ, and watch how its hiring changes over time.
• Lead generation — surface companies that are actively hiring, enriched with website, size and sector.
• Job-board & aggregator building — power your own board with clean, de-duplicated postings and full descriptions.
• Vacancy monitoring — schedule it with incremental mode + notifications for a live change feed of new openings.
• AI agents & pipelines — compact output plugs straight into LLM/MCP workflows.

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♻️ Incremental monitoring — pay for changes, not repeats

Schedule the actor and turn on incremental mode: each run compares against the last and emits only NEW / UPDATED / EXPIRED jobs — unchanged postings are skipped before their description is fetched, so a daily watch costs a fraction of a full re-scrape.

Daily churn	of 1,000 tracked	billable records	you save
5 %	1,000	50	95 %
15 %	1,000	150	85 %
30 %	1,000	300	70 %

The first run seeds the baseline and bills in full; every run after that bills only the delta. Reposts of the same role are flagged so you can suppress duplicates.

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🚀 How to run it

1. Open the actor and enter a search keyword (e.g. registered nurse) and a location — or paste a hiring.cafe URL.
2. Pick any filters (workplace type, commitment, seniority, posted-within days).
3. Set Max results and choose whether to fetch full descriptions.
4. (Optional) Turn on incremental mode and a notification channel, then Schedule it.
5. Click Start, then download the data as JSON, CSV or Excel, or pull it from the API.

New to Apify? Create a free account — it comes with monthly credit, no credit card required.

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🔌 Integrations & export

Export to JSON, CSV, Excel or an HTML table, or pull from the REST API and the JavaScript / Python clients. Runs on a schedule, connects to Google Sheets, Slack, Make, Zapier and n8n, and works as an MCP tool for AI agents — compact mode keeps token usage small.

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❓ FAQ

Do I need a proxy or login? No — it runs out of the box with no login and no proxy. Apify Proxy is available under Advanced for very high-volume runs.

Can I scrape all jobs at one specific company? Yes — paste that company's hiring.cafe page URL (e.g. hiring.cafe/org/stripe) into startUrls and it pulls every open role, with enriched company data.

Can I get only new jobs on a schedule? Yes — turn on incremental mode and schedule it; each run emits only what changed and can notify your channel.

Can I get remote-only jobs? Yes — set workplaceTypes to Remote (combine it with a keyword, location or seniority filter).

Does it work with n8n, Make or Zapier? Yes — it runs on a schedule and connects to n8n, Make, Zapier, Google Sheets and Slack, or any webhook.

How much does it cost? You pay only for the results you keep — and because incremental mode bills only changed jobs, scheduled monitoring costs a fraction of a full re-scrape.

Does it get salaries and full descriptions? Yes — normalized salary bands (where the employer discloses them) and full descriptions as text, HTML and Markdown.

What formats can I export? JSON, CSV, Excel, HTML table, or via the API.

Is it good for AI agents? Yes — enable compact mode; the output is MCP-friendly.

How many jobs can I get? As many as the search returns — set maxResults (0 = unlimited).

Is scraping this legal? The actor collects only publicly available data. You are responsible for how you use it, including any personal data and GDPR-style obligations.

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⚖️ Disclaimer

This actor accesses only publicly available data on hiring.cafe. You are responsible for how you use the extracted data — in particular any personal information — and for complying with the site's terms and applicable law (including the GDPR where it applies). Not affiliated with, endorsed by, or sponsored by hiring.cafe.

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