Naukri Jobs Scraper — salaries in USD, not Lacs

Scrape job listings from Naukri, India's largest job board, with pay converted out of Lac/Crore notation into plain rupees and an approximate USD figure — plus the salary disclosure rate, so you know how much of the market actually reports pay.

Unofficial. Not affiliated with, endorsed by, or connected to Naukri or Info Edge.

Why this one

Naukri reports pay the way Indian listings do:

2.25-3.5 Lacs PA        1 Lac   =    100,000 INR
1.5-2 Cr PA             1 Crore = 10,000,000 INR
Not disclosed

That notation is unreadable to most buyers outside India, and as a string it can't be sorted, averaged, or compared against a budget. This Actor returns:

Field	Example
salaryMinInr / salaryMaxInr	600000 / 1000000
salaryMidInr	800000
salaryMidUsd	9091
salaryUnit	LAC
salaryText	"6-10 Lacs PA"

The original string is always kept, so the conversion stays auditable. The exchange rate is yours to set (inrPerUsd, default 88) and is reported back in SALARY_SUMMARY, so you can recompute with a different rate without re-running.

Undisclosed pay is never zero

Most Naukri listings don't show pay. Rows without a figure get isSalaryDisclosed: false and null — not 0. Zero-filling would drag the median down and make the market look cheaper than it is. SALARY_SUMMARY reports salaryDisclosureRate so you can see how much of the sample the median is actually based on.

Other things made sortable

• experienceMinYears / experienceMaxYears from "0-4 Yrs"
• postedDaysAgo from "3 weeks ago" — filter out stale listings
• companyRating with companyReviewCount — a 4.8 from 3 reviews is not a 4.8 from 3,000

What you get

Per job: title, company, location, the salary fields above, experience range, company rating and review count, days since posting, skills, snippet, and URL.

A SALARY_SUMMARY record with salaryDisclosureRate, medianSalaryInr, medianSalaryUsd, medianExperienceMinYears, medianPostedDaysAgo, the inrPerUsd used, and the top hiring companies.

What this Actor does not do

• No personal data. Job listings are company data. No recruiter names, contacts, or profiles.
• No CAPTCHA solving or bot-detection bypass.
• No logged-in scraping. Public listing pages only.
• No applicant-side data. Nothing about who applied or viewed.

Reliability

Success rate was measured before this Actor was written: 18/18 fetches through the same browser path used in production. It is monitored twice daily against a live page.

Naukri is a Next.js app whose listings render client-side, so this Actor drives a real browser. Use useProxy: true with RESIDENTIAL.

Input

{
  "queries": ["data analyst", "software engineer"],
  "maxItemsPerQuery": 60,
  "inrPerUsd": 88,
  "useProxy": true,
  "proxyType": "RESIDENTIAL"
}

Plain search terms are turned into Naukri list URLs automatically. You can also pass full list URLs (https://www.naukri.com/data-analyst-jobs) if you've already filtered on the site.

Billing

Pay per event: one job-scraped event per job actually delivered to your dataset. Duplicates are removed before charging, and a run that returns nothing costs nothing.