Himalayas Real-Time Data

Live remote-job intelligence from Himalayas — one of the largest remote job boards. Search 100k+ verified remote positions by keyword, country, seniority, and contract type, walk the full feed, track hiring at specific companies, or refresh saved job URLs. Every record streams to your dataset as structured JSON the moment it is finalized.

Free trial: runs on the Apify free plan return a 2-result sample per run. Upgrade to a paid Apify plan for full, unlimited data.

Who this is for

• Recruiters & sourcing teams building remote talent pipelines and tracking who is hiring
• Job seekers & career coaches monitoring new remote openings by role, country, and seniority
• Startup researchers & investors watching hiring velocity at specific companies
• Salary analysts benchmarking remote pay ranges by role and region
• AI agents & automation builders feeding fresh remote-job data into CRMs, alerts, and dashboards

Use cases

1. Monitor new remote openings for a role (e.g. “product designer”) and push them to Slack daily
2. Build a target-employer watchlist and track every new opening at those companies
3. Benchmark remote salary ranges across roles, seniority levels, and countries
4. Backfill a job board or internal database from the full live feed
5. Refresh a saved shortlist of job URLs with current details
6. Power an AI job-matching agent with structured, always-fresh postings

Features

Feature	What it does	Default
💼 Job search	Keyword search with country, worldwide-only, seniority, employment-type, and sort filters	On (software engineer, 10 jobs)
✨ Fetch full details	Adds full description text + posting/expiry dates to the same row (detailsFetched: true)	Off
📡 Browse full feed	Walks the entire live feed, newest first, up to your cap	Off
🏢 Company jobs	Live openings at specific companies by slug (e.g. stripe, lemon-io)	Off
🔗 Scrape by URL	Full records from explicit Himalayas job URLs	Off
📣 Delivery	JSON or Slack webhook push per record, plus streaming dataset writes	Optional

Every discovered job is exported. Filtering never drops rows: with enrichment off you get fast cards; with it on, the same rows carry full details.

Input reference

• enableJobSearch (boolean, default true) — run keyword searches.
• jobKeywords (string list, default ["software engineer"]) — one search runs per keyword.
• jobCountry (string, default "") — e.g. "United States", "Germany". Empty = worldwide.
• worldwideOnly (boolean, default false) — only jobs open worldwide.
• seniority (string list, default []) — any of Entry-level, Mid-level, Senior, Manager, Director, Executive.
• employmentType (string list, default []) — any of Full Time, Part Time, Contractor, Temporary, Intern, Volunteer, Other.
• jobSort (string, default "relevant") — relevant | recent | salaryAsc | salaryDesc | nameAToZ | nameZToA | jobs.
• jobsPerQuery (integer, default 10, max 1000) — cap per keyword search.
• fetchFullDetails (boolean, default false) — enrich rows in place.
• enableBrowseFeed (boolean, default false) + feedMaxJobs (integer, default 10, max 5000).
• enableCompanyJobs (boolean, default false) + companySlugs (string list, e.g. ["stripe"]) + jobsPerCompany (integer, default 10).
• enableScrapeByUrl (boolean, default false) + jobUrls (string list of himalayas.app/companies/.../jobs/... URLs).
• webhookUrl (string) + webhookFormat (json | slack).
• proxyConfiguration (proxy) — Residential US proxies recommended.

Empty input still runs a useful demo: job search for software engineer, 10 jobs.

Output fields

Each dataset row is one job: featureType, jobId, title, company, companySlug, companyLogo, location, locationRestrictions, timezoneRestrictions, salary, salaryMin, salaryMax, salaryCurrency, salaryPeriod, snippet, categories, seniority, postedAt, expiryDate, employmentType, descriptionText (with enrichment / URL rows), detailsFetched, jobUrl, applicationLink, searchQuery, searchCountry, position, source, scrapedAt.

The run OUTPUT includes totalPushed, enabledFeatures, errors, and a paywall object (detected, isPaying, pricingTier, limited, blocked, freeTierMaxItems).

Webhooks

Set webhookUrl to receive each record in real time in addition to the dataset write. json delivers the raw record; slack delivers a formatted message with title, company, location, salary, and link. Delivery is fire-and-forget: failures are logged and never stop the run.

MCP / AI-agent usage

Pair with the Apify MCP server: connect your agent, start this Actor with a role keyword, then ask questions over the dataset.

Example prompt: “Using the latest Himalayas Real-Time Data run for ‘customer success’, which remote-first companies posted this week and what pay ranges did they list?”

FAQ

• Which proxy should I use? Residential proxies (US default) give the freshest results. Local runs use the DataImpulse residential gateway via .env.
• What does the free tier include? A 2-result sample per run so you can verify the schema. Upgrade for unlimited rows.
• How fresh is the data? Every run collects live listings at run time — what you get is what is posted right now.
• Do detail rows cost more? The result pay-per-event charge applies per exported row; enrichment adds a little extra time per record but no extra rows.