Naukri Job Scraper

hipersoft/naukri-scraper

Search Naukri.com and scrape job listings: title, company, salary, experience, location, skills, description and link. For recruitment, market research and lead generation.

Run this scraper →See the API call

Total users

Monthly users

Total runs

102

Per job scraped

$0.0043

Last rebuilt

Oct 28, 2026

Overview

Scrape Naukri.com — India's #1 job portal — into clean JSON, CSV, Excel or XML. Search any keyword and get job title, company, company rating, salary, experience range, required skills, location, posted date and apply URL for every listing. Fast and reliable.

Naukri Scraper input — keywords, location and experience in the Apify Console

What does the Naukri Scraper do?

The Naukri Scraper extracts job listings from Naukri.com by keyword and location, returning a structured record for every job — role, employer, salary, experience band, skills and freshness. Use it to build hiring datasets, benchmark salaries and skills, or feed recruitment and market-research pipelines across India.

What data can you scrape from Naukri?

💼 Job — title, full description, Naukri apply URL
🏢 Company — name, ID, AmbitionBox rating + review count, logo
💰 Salary & experience — salary label, currency, min/max years
🧠 Skills — parsed list of required skills and tags
📍 Location — city and work mode (on-site, remote, hybrid)
🕐 Freshness — posted label, posted date, walk-in flag

Use cases

Recruitment & sourcing — build live feeds of open roles for any keyword or city.
Salary benchmarking — compare salary bands across companies and experience levels.
Skills research — track which skills employers demand for a role over time.
Labour-market analysis — measure hiring volume and freshness by city and sector.
B2B lead generation — identify companies that are actively hiring.
Competitive intelligence — monitor a competitor's open roles and headcount signals.

How to scrape Naukri data

Add the Naukri Scraper to your Apify account.
Enter one or more keywords (job titles or search terms), one per line.
Optionally set a location, experience filter and sort order.
Set maxItemsPerKeyword to cap results, then click Run.
Export the dataset as JSON, CSV, Excel or XML, or pull it via the Apify API.

Input

keywords — job titles / search terms, one per line (e.g. software engineer, data analyst, sales manager)
location — optional city (e.g. bangalore, mumbai, delhi-ncr)
experience — optional years-of-experience filter
sort — Relevance or Freshness
maxItemsPerKeyword — cap jobs per keyword (20 per page)

Example input

{ "keywords": ["software engineer", "data analyst"], "location": "bangalore", "maxItemsPerKeyword": 200 }

What you get

Naukri Scraper output example — job listings with company, salary and skills as structured JSON

{
  "id": "290726921897",
  "title": "Software Engineer",
  "company": "Wells Fargo",
  "companyRating": 3.6,
  "companyReviews": 9035,
  "experience": "0-5 Yrs",
  "salary": "Not disclosed",
  "currency": "INR",
  "location": "Bengaluru",
  "skills": ["Java", "Azure", "APIs", "Microservices"],
  "description": "2+ years of software engineering experience…",
  "postedLabel": "1 Day Ago",
  "createdDate": "2026-07-29T11:16:54.791Z",
  "url": "https://www.naukri.com/job-listings-software-engineer-wells-fargo-bengaluru-0-to-5-years-290726921897",
  "sourceUrl": "https://www.naukri.com",
  "collectedAt": "2026-07-30T22:18:54.613Z"
}

Every record has a stable id, sourceUrl, collectedAt and explicit null for missing fields.

Output schema

Field	Type	Description
`id`	string	Unique Naukri listing identifier for the job.
`title`	string	Job title / role.
`company`	string	Name of the hiring company.
`companyId`	string	Naukri's internal identifier for the company.
`companyRating`	number	Company's AmbitionBox star rating.
`companyReviews`	integer	Number of employee reviews behind the rating.
`experience`	string	Experience requirement label (e.g. `0-5 Yrs`).
`minExperience`	string	Minimum years of experience required.
`maxExperience`	string	Maximum years of experience considered.
`salary`	string	Salary label as shown on the listing.
`currency`	string	Currency code for the salary (e.g. `INR`).
`location`	string	Job location / city.
`skills`	array	List of required skills or tags.
`description`	string	Job description text.
`postedLabel`	string	Human-readable posting age (e.g. `1 Day Ago`).
`createdDate`	string (ISO date)	Timestamp when the listing was posted.
`mode`	string	Work mode (on-site, remote or hybrid).
`isWalkin`	boolean	Whether the job is a walk-in interview.
`logoUrl`	string (URL)	Company logo image URL.
`url`	string (URL)	Direct link to the job listing on Naukri.
`sourceUrl`	string (URL)	Source site URL.
`collectedAt`	string (ISO date)	Timestamp when the record was collected.

Need more job data?

FAQ

How many jobs can I scrape? As many as the search returns — set maxItemsPerKeyword to control the volume per keyword.

Do I need any setup or login? No setup and no login. Just add your keywords and inputs, then run.

How does billing work? You pay per result you get — no wasted spend on empty runs.

What export formats are supported? JSON, CSV, Excel and XML, plus the Apify API for programmatic access.

How fresh is the data? Each run fetches live listings and stamps every record with collectedAt; sort by Freshness for the newest jobs.

Can I filter by location or experience? Yes — use the location and experience inputs to narrow results.

Can I connect it to other tools? The Naukri Scraper can be connected with almost any cloud service or web app thanks to integrations on the Apify platform. It works with Make, Zapier, Slack, Airbyte, GitHub, Google Drive and many more, plus the Apify API, JavaScript/Python clients and MCP. Or use webhooks to trigger an action whenever a run finishes.

Notes

Original clean-room implementation. Returns only public data; you are responsible for compliance with Naukri.com's terms. Not affiliated with Naukri.com or Info Edge.

Input

Field	Type	Description
`keywords` Keywords / job titles	array	Search terms, one per line (e.g. "software engineer", "data analyst", "sales manager").
`location` Location	string	Optional city filter (e.g. "bangalore", "mumbai", "delhi-ncr"). Leave blank for all India.
`experience` Experience (years)	string	Optional years-of-experience filter (e.g. "3"). Leave blank for any.
`maxItemsPerKeyword` Max jobs per keyword	integer	Cap jobs per keyword (20 per page). Default: `200`
`sort` Sort order	string · r, f	Result order. Default: `"r"`

API

curl -X POST "https://api.apify.com/v2/acts/hipersoft~naukri-scraper/run-sync-get-dataset-items?token=$APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
  "keywords": [
    "software engineer"
  ]
}'

from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")
run = client.actor("hipersoft/naukri-scraper").call(run_input={
    "keywords": [
        "software engineer"
    ]
})

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_APIFY_TOKEN' });
const run = await client.actor('hipersoft/naukri-scraper').call({
  "keywords": [
    "software engineer"
  ]
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

Pricing

Event	Price	Paid plans from
Job scraped One job listing scraped (with company rating, salary, experience and skills).	$0.0043	$0.0021
API request One Naukri job-search API request (a page of ~20 jobs).	$0.001	$0.001

You pay only for what the run returns. Set a maximum cost per run and it stops cleanly at that limit.

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