Jobs Data Scraper 🚀 — Enterprise‑ready Job Listings & Salary Insights

Extract fresh job postings and salary intelligence at scale. Configure powerful queries, paginate reliably, and enrich with job details and salary insights — all in one Apify Actor.

• Primary keywords: Jobs Data Scraper, Job Listings API, Job Search Scraper, Salary Data Scraper, Company Salary Insights
• Related keywords: Job aggregation, job details API, estimated salary, company salary by title, job analytics, job market data, hiring intelligence, recruitment automation

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Why use this Jobs Data Scraper? ✨

• Unified coverage: Search jobs + fetch details + estimate salaries + analyze company salary bands.
• Flexible filters: Location, posting recency, language, and more.
• Scalable & resilient: Built for batching, retries, and high‑volume dataset writes.
• Clean JSON: Outputs ready for CRMs, data warehouses, and analytics.

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Endpoints Overview 🧭

Endpoint	Purpose	Typical Use Cases
/search	Search for jobs posted on public job sites across the web (largest aggregation). Extensive filtering support.	Job market scans, competitive hiring analysis, candidate sourcing
/job-details	Get all job details by job_id, including employer reviews, extra application links, similar job salary hints.	Enrichment, application path analysis, employer research
/estimated-salary	Get salary/pay estimates for a job title around a location.	Compensation benchmarking, offer calibration
/company-job-salary	Get salary/pay in a specific company per job title and optionally a location.	Company pay bands, role-wise salary analysis

Tip: Run any combination of these in a single Actor run.

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Input Configuration (Apify UI) ⚙️

Global inputs (affect multiple endpoints):

Key	Type	Default	Description
country	string	us	2-letter country code (e.g., us, gb, in).
language	string	en	Language code (e.g., en).
date_posted	enum	all	Recency filter: all, today, 3days, week, month.

Run only what you need by toggling the endpoint-specific flags below.

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1) /search — Job Search Across the Web 🔎

Search jobs from the largest public job aggregations with extensive filtering. Ideal for discovering roles by title, location keywords, and more.

• Enable: Provide query (search runs when query is present)
• Inputs:

Key	Type	Default	Description
query	string	required	e.g., marketing manager in new york via linkedin
page	integer	1	Start page (1-based).
num_pages	integer	1	Number of pages to fetch from page.
country	string	us	Country filter.
date_posted	enum	all	all, today, 3days, week, month.
language	string	en	Language filter.

• Example input:

{
  "query": "marketing manager in new york via linkedin",
  "page": 1,
  "num_pages": 1,
  "country": "us",
  "date_posted": "all",
  "language": "en"
}

• Example output item (fields vary by source):

{
  "job_id": "-uNPnvjFRt1PgXtJAAAAAA==",
  "job_title": "Market Manager, New York (Remote)",
  "employer_name": "Weedmaps",
  "job_publisher": "LinkedIn",
  "job_apply_link": "https://www.linkedin.com/jobs/view/...",
  "job_description": "...",
  "job_is_remote": true,
  "job_posted_at": "4 hours ago",
  "job_location": "New York, NY",
  "job_city": "New York",
  "job_state": "New York",
  "job_country": "US",
  "job_min_salary": 99115,
  "job_max_salary": 110950,
  "job_salary_period": "YEAR"
}

---

2) /job-details — Deep Job Enrichment 🧩

Fetch complete job details by job_id. Includes all search fields plus enrichment such as employer reviews, alternative application links, and similar job salary estimates.

• Enable: details_enabled: true
• Inputs:

Key	Type	Default	Description
details_enabled	boolean	false	Toggle job-details fetching.
details_job_ids	array[string]	[]	One or more job IDs to enrich.
country	string	us	Country context when resolving details.

• Example input:

{
  "details_enabled": true,
  "details_job_ids": ["-uNPnvjFRt1PgXtJAAAAAA=="],
  "country": "us"
}

• Output:
  • Array of enriched job objects; this Actor tags them with "_type": "job_details" to distinguish in the dataset.

---

3) /estimated-salary — Title & Location Based Salary 💸

Estimate salary for a given job title around a target location. Use it to calibrate offers or benchmark compensation quickly.

• Enable: salary_enabled: true
• Inputs:

Key	Type	Default	Description
salary_enabled	boolean	false	Toggle estimated-salary.
salary_job_title	string	required	e.g., marketing manager.
salary_location	string	required	e.g., new york, ny.
years_of_experience	enum	ALL	Experience band: ALL, LESS_THAN_ONE, ONE_TO_THREE, FOUR_TO_SIX, SEVEN_TO_NINE, TEN_TO_FOURTEEN, ABOVE_FIFTEEN.
salary_location_type	enum	ANY	Location type: ANY, CITY, STATE, COUNTRY.

• Example input:

{
  "salary_enabled": true,
  "salary_job_title": "marketing manager",
  "salary_location": "new york, ny",
  "years_of_experience": "ONE_TO_THREE",
  "salary_location_type": "CITY"
}

• Output:
  • Salary estimate objects; this Actor tags them with "_type": "estimated_salary" and echoes job_title, location, years_of_experience, salary_location_type.

---

4) /company-job-salary — Company‑Specific Pay Bands 🏢💼

Analyze salary by job title within a specific company, optionally filtered by location. Great for employer-level pay transparency and role‑wise comparisons.

• Enable: company_salary_enabled: true
• Inputs:

Key	Type	Default	Description
company_salary_enabled	boolean	false	Toggle company-job-salary.
company_salary_company	string	required	Company name (e.g., Google).
company_salary_job_title	string	""	Optional job title filter.
company_salary_location	string	""	Optional location filter (e.g., new york, ny).
company_salary_years_of_experience	enum	ALL	Experience band: ALL, LESS_THAN_ONE, ONE_TO_THREE, FOUR_TO_SIX, SEVEN_TO_NINE, TEN_TO_FOURTEEN, ABOVE_FIFTEEN.
company_salary_location_type	enum	ANY	Location type: ANY, CITY, STATE, COUNTRY.

• Example input:

{
  "company_salary_enabled": true,
  "company_salary_company": "Google",
  "company_salary_job_title": "marketing manager",
  "company_salary_location": "new york, ny",
  "company_salary_years_of_experience": "FOUR_TO_SIX",
  "company_salary_location_type": "CITY"
}

• Output:
  • Company salary items; this Actor tags them with "_type": "company_job_salary" and echoes company, job_title (if any), location (if any), company_salary_years_of_experience, and company_salary_location_type.

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Best Practices ✅

• Start narrow: Test with num_pages: 1 to validate output shape and volume.
• Use enrichment selectively: Run /search to collect job_ids, then /job-details only for those you need.
• Normalize downstream: Dataset items come from different sources; keep a transformation step for your warehouse.
• Respect quotas: If you run large details_job_ids lists or many salary lookups, batch thoughtfully.

---

Example Combined Run 🧪

{
  "query": "marketing manager in new york via linkedin",
  "page": 1,
  "num_pages": 1,
  "country": "us",
  "date_posted": "week",
  "language": "en",

  "details_enabled": true,
  "details_job_ids": ["-uNPnvjFRt1PgXtJAAAAAA=="],

  "salary_enabled": true,
  "salary_job_title": "marketing manager",
  "salary_location": "new york, ny",
  "salary_period": "YEAR",

  "company_salary_enabled": true,
  "company_salary_company": "Google",
  "company_salary_job_title": "marketing manager",
  "company_salary_location": "new york, ny",
  "company_salary_period": "YEAR"
}

---

FAQs ❓

• Where do results go?
  To the run’s default Apify dataset as JSON items. Each item may include a _type to identify the endpoint (e.g., job_details, estimated_salary, company_job_salary).

• Can I run only one endpoint?
  Yes. Provide only the inputs for the endpoint(s) you want. For example, omit details_enabled if you only want /search.

• How are salary estimates scoped?
  Controlled by years_of_experience / company_salary_years_of_experience (experience band) and salary_location_type / company_salary_location_type (location granularity).

• How do I filter recent postings?
  Use date_posted: today, 3days, week, or month.

• Which country and language are supported?
  Use ISO‑2 country codes (e.g., us, gb) and standard language codes (e.g., en). Availability of roles may vary by market.

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Jobs Scraper Keywords & Hashtags 🔍

• Keywords: job listings scraper, job postings API, job search data, job enrichment, employer reviews, job application links, salary scrape, compensation insights, HR analytics, recruitment data automation, linkedin job scraper, naukri job scraper, monster job scraper, glassdoor job scraper, remoteok job scraper, weworkremotely job scraper, toptal job scraper, freelancer job scraper, jobstreet job scraper, careerbuilder job scraper, workopolis job scraper, ziprecruiter job scraper, dice job scraper, shine job scraper, simplyhired job scraper, angel job scraper, hired job scraper
• Hashtags:
  #JobScraper #JobsData #RecruitmentTech #HRAnalytics #SalaryInsights
#HiringIntelligence #PeopleOps #Compensation #DataEngineering #Apify

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Job Sites Aggregation 📊

indeed.com

linkedin.com

naukri.com

monster.com

glassdoor.com

rozee.pk

bayt.com

careerbuilder.com

workopolis.com

ziprecruiter.com

dice.com

jobstreet.com

shine.com

simplyhired.com

angel.co

hired.com

remoteok.com

weworkremotely.com

toptal.com

freelancer.com