India Job Listings & Salary Data Scraper — Naukri.com

India job listings with salary data, from Naukri.com — India's largest job portal, 100M+ registered users and 700K+ active listings. Search by keyword, location, experience level, and work arrangement; returns job title, company and rating, salary range, required skills, posting age, and the work-from-home flag per listing.

What it does

The actor returns fully structured job records — not scraped page text, so fields stay clean and stable when Naukri restyles its listings. It paginates automatically until your maxItems limit is reached or results are exhausted.

Input: keyword + optional filters → Output: one record per job listing with 17 structured fields.

Use cases

• Job market research — track salary ranges, required skills, and hiring trends across companies and locations
• Talent intelligence — identify which companies are actively hiring for a given role
• Competitive analysis — monitor competitor job postings and growth signals
• HR analytics — bulk-gather job data for compensation benchmarking or skills gap analysis
• Recruiting tools — feed structured job data into your own applications or databases

Input

Field	Type	Description
keyword	string (required)	Job search term, e.g. python developer, data scientist, product manager
location	string	City or region, e.g. Bangalore, Mumbai, Delhi NCR. Leave blank for all India.
experienceMin	integer	Minimum years of experience. Use 0 for fresher-friendly jobs. Default: 0
experienceMax	integer	Maximum years of experience. Leave blank for no upper limit.
workType	string	Work arrangement filter: work from home, hybrid, on-site. Leave blank for all.
maxItems	integer	Maximum number of listings to scrape. Default: 10

Example input

{
  "keyword": "python developer",
  "location": "bangalore",
  "experienceMin": 2,
  "experienceMax": 7,
  "workType": "",
  "maxItems": 100
}

Output

Each record contains:

Field	Description
jobId	Naukri internal job ID
title	Job title
companyName	Hiring company name
companyRating	Company rating on Naukri (0–5 scale, as string)
salary	Salary range as displayed (e.g. 10-20 Lacs PA)
experience	Required experience range (e.g. 2-5 Yrs)
location	Job location(s)
skills	Required skills, comma-separated
jobDescription	Full job description text
postedOn	Date posted (Unix timestamp as string)
jobAge	Human-readable posting age (e.g. 3 Days Ago, 30+ Days Ago)
jobUrl	Direct link to the job detail page
isWork_from_home	"true" if work-from-home eligible
isFresher	"true" if the role is open to freshers (0 years experience required)
tags	Naukri listing tags
footerPlaceholderLabel	Footer context label (e.g. Recruiting actively)
scrapedAt	ISO 8601 timestamp when the record was scraped

Example output record

{
  "jobId": "87654321",
  "title": "Senior Python Developer",
  "companyName": "Infosys",
  "companyRating": "3.9",
  "salary": "12-20 Lacs PA",
  "experience": "3-6 Yrs",
  "location": "Bengaluru",
  "skills": "Python, Django, REST APIs, AWS",
  "jobDescription": "We are looking for an experienced Python developer...",
  "postedOn": "1748390400000",
  "jobAge": "5 Days Ago",
  "jobUrl": "https://www.naukri.com/job-listings/senior-python-developer-87654321",
  "isWork_from_home": "false",
  "isFresher": "false",
  "tags": "",
  "footerPlaceholderLabel": "Recruiting actively",
  "scrapedAt": "2026-05-28T10:00:00.000Z"
}

Notes

• No surcharges — infrastructure is on us; you pay for records, not overhead.
• Rate limiting — A 3-second delay between page requests respects Naukri's servers and avoids blocks.
• Experience filter — experienceMin is passed server-side. experienceMax is applied client-side (the API does not support it natively).
• Pagination — Naukri returns up to 20 results per page; the actor paginates automatically to reach your maxItems target.
• Freshers — Set experienceMin: 0 for fresher-friendly listings; filter further with isFresher: "true" in your output.

Pricing

Priced per result record (Pay Per Event). You are charged only for data you receive.

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Further reading: Job Postings Data: How to Get Listings From 12 Boards Across 10 Markets