Himalayas Job Scraper

What does Himalayas Job Scraper do?

Himalayas Job Scraper collects remote job listings from Himalayas.app and saves them as structured records. Search by a keyword and location, or provide a public Himalayas jobs URL, then export job titles, companies, compensation, location requirements, descriptions, employment types, and application links for recruiting, hiring intelligence, market research, and job-board monitoring.

The simplest run uses keyword and location. You can also set startUrl when you already have a Himalayas search page you want to collect. Results are saved to an Apify dataset in JSON, CSV, Excel, XML, and other supported formats.

Why use Himalayas Job Scraper?

• Build a remote hiring dataset - Collect job listings from selected searches and keep the important fields together for analysis.
• Support recruitment sourcing - Find roles by title, skill, or location and pass the resulting job URLs to your recruiting workflow.
• Track compensation and requirements - Compare published salary ranges, employment types, seniority, location restrictions, and time zones.
• Monitor new opportunities - Run the Actor on a schedule and compare datasets over time to follow hiring activity.
• Choose the right level of detail - Use collectDetails: true for descriptions and the source job object, or disable it for lighter monitoring runs.
• Connect results to other systems - Use dataset exports, webhooks, integrations, or the Apify API in dashboards, spreadsheets, CRMs, and automation tools.

What data can you extract from Himalayas.app?

Each dataset item represents one job listing. Empty source values are omitted, so records can have different sets of fields.

Field	Type	Description
title	String	Job title.
excerpt	String	Short listing summary when available.
company	String	Hiring company name.
company_slug	String	Company identifier from the listing.
company_logo	String	Company logo URL when published.
location	String	Consolidated applicant location, or Worldwide when no restriction is provided.
applicant_location_requirements	Array	Countries or regions where applicants can be located.
timezone_restrictions	Array	Allowed timezone offsets when published by the job.
categories	Array	Job categories or tags.
parent_categories	Array	Parent category labels.
date_posted	String	Posting date in ISO 8601 format.
apply_before	String	Application deadline in ISO 8601 format when available.
Description_html	String	Sanitized rich-text job description.
Description_text	String	Plain-text version of the job description.
salary	String	Human-readable salary range and currency.
salary_min	Number	Minimum published salary.
salary_max	Number	Maximum published salary.
salary_currency	String	Published salary currency code.
job_type	String	Primary employment type, such as full time or contract.
employment_types	Array	Employment types listed for the job.
remote	Boolean	Whether the listing is marked as remote.
seniority	Array	Seniority labels published by the source.
raw_job	Object	Full source job object when collectDetails is enabled.
url	String	Canonical application or job listing URL.
source	String	Source label, normally himalayas.app.
scraped_at	String	ISO 8601 timestamp for the collection.

How to scrape Himalayas job listings

1. Open Himalayas Job Scraper in Apify Console.
2. Enter a keyword and optional location, or provide a public Himalayas jobs page in startUrl.
3. Set results_wanted and max_pages for the size of the run.
4. Keep collectDetails enabled when you need full descriptions and enriched fields.
5. Start the run and review the dataset preview.
6. Download the results or connect the dataset to your workflow.

If startUrl is provided, the Actor uses that URL as the starting point. When no search filters are supplied, it can collect from the general Himalayas jobs listing.

Input Parameters

Parameter	Type	Required	Default or prefill	Description
startUrl	String	No	https://himalayas.app/jobs	Public Himalayas jobs or search URL to use as the starting point. A URL with search parameters can preserve those filters.
keyword	String	No	software engineer	Job title, skill, or phrase to search for when startUrl is not used for the search.
location	String	No	United States	Country or location filter for keyword-based searches.
collectDetails	Boolean	No	true	Include the full description fields and raw_job object when available.
results_wanted	Integer	No	20	Maximum number of job records to save.
max_pages	Integer	No	5	Maximum number of result pages to process.
proxyConfiguration	Object	No	{"useApifyProxy": false}	Optional Apify Proxy settings for the run.

All parameters are optional. The Actor uses its standard search and result limits when you leave them empty.

Output Data

The Actor writes one record per job to the default dataset. raw_job is included only when collectDetails is true; source fields without a value are omitted.

Field	Type	Description
title	String	Position title.
company	String	Employer or hiring organization.
location	String	Remote location requirements.
salary	String	Formatted compensation summary when available.
job_type	String	Primary employment type.
date_posted	String	ISO 8601 posting timestamp.
apply_before	String	ISO 8601 deadline when available.
Description_text	String	Plain-text description for search and analysis.
Description_html	String	Sanitized rich-text description.
categories	Array	Job category labels.
seniority	Array	Seniority labels.
url	String	Direct job or application URL.
source	String	Source website label.
scraped_at	String	Collection timestamp.
raw_job	Object	Additional source data when detailed collection is enabled.

Usage Examples

Basic keyword search

Collect up to 20 software engineering jobs associated with the United States.

{
  "keyword": "software engineer",
  "location": "United States",
  "results_wanted": 20
}

Collect from a Himalayas search URL

Start from a public search page and collect more results across several pages.

{
  "startUrl": "https://himalayas.app/jobs?q=data+engineer",
  "results_wanted": 100,
  "max_pages": 8,
  "collectDetails": true
}

Focused monitoring run

Collect customer success roles for Canada while keeping the run lighter by omitting the full source job object.

{
  "keyword": "customer success",
  "location": "Canada",
  "collectDetails": false,
  "results_wanted": 50,
  "max_pages": 5
}

Sample Output

This example shows one dataset item with the main fields available from a detailed run. Some fields may be omitted when the listing does not publish them.

{
  "title": "Senior Data Engineer",
  "excerpt": "Build scalable data systems for global analytics workloads.",
  "company": "Example Labs",
  "company_slug": "example-labs",
  "company_logo": "https://cdn-images.himalayas.app/example-logo",
  "location": "United States, Canada",
  "applicant_location_requirements": ["United States", "Canada"],
  "timezone_restrictions": [-8, -7, -6, -5],
  "categories": ["Data-Engineer", "Software-Engineer"],
  "parent_categories": ["Developer"],
  "date_posted": "2026-04-01T10:22:00.000Z",
  "apply_before": "2026-05-01T10:22:00.000Z",
  "Description_html": "We are looking for a senior data engineer to build scalable data systems.",
  "Description_text": "We are looking for a senior data engineer to build scalable data systems.",
  "salary": "120000-160000 USD",
  "salary_min": 120000,
  "salary_max": 160000,
  "salary_currency": "USD",
  "job_type": "Full Time",
  "employment_types": ["Full Time"],
  "remote": true,
  "seniority": ["Senior"],
  "url": "https://himalayas.app/companies/example-labs/jobs/senior-data-engineer",
  "source": "himalayas.app",
  "scraped_at": "2026-04-08T08:35:12.220Z",
  "raw_job": {
    "title": "Senior Data Engineer",
    "companyName": "Example Labs"
  }
}

Tips for best results

• Start with a small limit - Test 20 to 50 results before increasing results_wanted or max_pages.
• Use focused keywords - Queries such as backend engineer, Python developer, or product designer usually produce more useful datasets than broad terms.
• Combine keyword and location - Use both filters when your workflow is limited to a country or hiring market.
• Enable details when needed - Detailed collection provides descriptions and raw_job; disable it for faster availability checks.
• Review source timestamps - Job listings can be edited, closed, or removed after collection, so use scraped_at when comparing runs.
• Use a schedule for monitoring - Schedule repeat runs in Apify and send new datasets to your alerting or reporting workflow.

Integrations and export formats

• Google Sheets or Airtable - Review roles, assign sourcing tasks, and maintain a searchable hiring list.
• Slack - Send selected job records to recruiting or market-monitoring channels.
• Make or Zapier - Trigger follow-up actions when a run completes.
• Webhooks - Deliver run notifications and dataset links to another service.
• Apify API - Start runs and retrieve dataset items from your own application.
• JSON, CSV, Excel, and XML - Download the dataset in the format that fits your analysis or import process.

Frequently Asked Questions

Can I run the Actor with only a keyword?

Yes. Provide keyword and leave location empty when you want results across locations.

Can I use a saved Himalayas search URL?

Yes. Put the public search page in startUrl. The Actor can use search parameters included in that URL as the starting filters.

Why is a salary field missing?

Salary fields are missing when the job listing does not publish compensation information. The Actor omits empty values instead of creating misleading amounts.

Does the Actor return full job descriptions?

Yes, when collectDetails is true and the source listing provides a description. The dataset can include both Description_html and Description_text.

Can I run this Actor on a schedule?

Yes. Apify schedules can run the Actor hourly, daily, weekly, or at another interval for recurring job-market monitoring.

Can I export Himalayas jobs to CSV or Excel?

Yes. Apify dataset exports include CSV, Excel, JSON, XML, and other supported formats.

Is it legal to collect data from Himalayas.app?

The Actor is intended for responsible collection of publicly available job information. You are responsible for following Himalayas.app terms, applicable laws, privacy requirements, and any restrictions on storing or redistributing job data.

Related Actors

• Kariyer Job Scraper - Collect structured job listings from Kariyer.net.
• Foundit Jobs Scraper - Gather job postings from Foundit, formerly Monster.
• Talent Job Scraper - Collect job listings from Talent.com for hiring research and monitoring.

Support

For issues, feature requests, or missing fields, use the Issues tab on the Actor page and include the input used, run ID, and an example of the affected listing when possible.

Legal Notice

This Actor is designed for legitimate job research, recruitment, monitoring, and data-analysis workflows using publicly available information. Users are responsible for complying with Himalayas.app terms, applicable laws, privacy obligations, and the rules of any system where the collected data is used.