Naukri.com Jobs Scraper
JOBSAUTOMATION
Naukri.com Jobs Scraper
Scrape job listings from Naukri.com, India's largest job portal with 100M+ registered users and 700K+ active job listings. Search by keyword, location, experience level, and work arrangement to extract structured job data at scale.
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 —
experienceMinis passed server-side.experienceMaxis 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
maxItemstarget. - Freshers — Set
experienceMin: 0for fresher-friendly listings; filter further withisFresher: "true"in your output.
Pricing
Priced per result record (Pay Per Event). You are charged only for data you receive.
Further reading: Job Postings Data: How to Get Listings From 12 Boards Across 10 Markets