Naukri Jobs Scraper — scrape Naukri.com job listings from India

Get structured job data from Naukri.com, India's largest job portal, by keyword and city. Every listing comes back with the employer's AmbitionBox rating, the experience range, parsed skills and a job description — and optionally, where Naukri serves it, how many people have already applied.

No login, no Naukri account, no API key. Export to JSON, CSV or Excel, or pull it straight from the Apify API.

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What this scraper gets you

Job	title, absolute URL, posted date (real ISO timestamp), vacancies, walk-in flag
Company	name, Naukri careers page, logo, AmbitionBox employee rating, reviews link
Money	salary band, currency, and an explicit salaryDisclosed flag
Fit	experience range (parsed to min/max), skills as a clean list, location
Demand ⭐	applicant count and view count per listing
Context ⭐	full description, industry, functional area, role category, education, company profile

⭐ = included when fullDescription is enabled.

Applicant counts turn a job board into a demand signal. In a 10-row Mumbai data-analyst run the median listing had 2,186 applicants and 5,196 views, and the most contested — Data Analyst at ICICI Lombard — had 7,913 applicants. That changes what you do with a posting, whether you are a jobseeker deciding where to spend effort, a recruiter pricing a role, or an analyst measuring real demand rather than counting adverts.

fullDescription is off by default because it adds one request per job and a per-job charge. It is fast: a measured 120-row run across four searches enriched 120 of 120 and finished in 16 seconds. descriptionIsFull marks each row either way, so a rare miss is always visible rather than silent. The run completes regardless, and every row still ships with its full search-level data.

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Quick start

{
  "keyword": "python developer",
  "location": "bangalore",
  "maxItems": 100
}

Several roles and cities in one run:

{
  "keywords": ["data analyst", "business analyst"],
  "locations": ["bangalore", "mumbai", "pune"],
  "maxItems": 600,
  "workMode": "remote"
}

That's 6 searches. They run interleaved, so stopping at maxItems leaves you with every combination covered instead of 600 rows from one city. De-duplication is global — a job listed in three cities is stored, and billed, once. Every row carries searchKeyword and searchLocation so you always know which search produced it.

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Input

field	default	what it does
keyword	python developer	job title, skill or keyword
location	bangalore	Indian city; blank searches all of India
keywords	—	several keywords at once; overrides keyword
locations	—	several cities at once; overrides location
maxItems	50	exact stop — you get the number you asked for
fullDescription	false	complete description + applicant/view counts (slower)
daysOld	—	only jobs posted in the last N days
experience	—	years of experience
workMode	—	remote, hybrid or office
salaryBand	—	0to3 … 75to100, lakhs per annum
maxPages	200	per-search safety cap
proxyConfiguration	RESIDENTIAL	Naukri is behind Akamai; residential is the safe default

Filters that actually filter

Each one was measured against a known baseline of 11,276 jobs (python developer / Bangalore) before it was exposed:

filter	result
experience 0 / 3 / 8	339 / 3,884 / 6,364
daysOld 1 / 3 / 7 / 15	352 / 899 / 1,819 / 3,781
salaryBand 0to3 / 3to6 / 6to10	862 / 3,926 / 6,373
workMode: remote	every returned row's location reads Remote

Naukri also publishes an employment-type facet and a role-category facet. Both were tested; both return the unfiltered count. They are deliberately not offered here — a filter that silently ignores you is worse than no filter.

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Output

{
  "jobId": "240826007480",
  "title": "Python Software Developer",
  "url": "https://www.naukri.com/job-listings-python-software-developer-capgemini-...",
  "companyName": "Capgemini",
  "companyRating": "3.6",
  "companyReviewsUrl": "https://www.ambitionbox.com/reviews/capgemini-reviews",
  "location": "Hybrid - Hyderabad, Pune, Bengaluru",
  "experienceText": "6-11 Yrs",
  "minimumExperience": "6",
  "maximumExperience": "11",
  "salaryText": "Not disclosed",
  "salaryDisclosed": false,
  "skills": ["API", "Python", "Rest", "Django", "Cloud", "Fast API"],
  "postedAt": "2026-09-21T11:37:26+00:00",
  "vacancies": 6,
  "applyCount": 2493,
  "viewCount": 7423,
  "industry": "IT Services & Consulting",
  "employmentType": "Full Time, Permanent",
  "educationUG": ["Any Graduate"]
}

47 fields per row. Detail-only fields are always present — null when fullDescription is off — so the column set never changes between runs.

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Two honest notes before you buy

Most Indian listings do not publish a salary. That is the market, not the scraper. Disclosure ran 11% in a Bangalore python-developer sample and 27% in a Mumbai data-analyst one. salaryDisclosed tells you which is which, and minimumSalary / maximumSalary are null rather than 0 when hidden, so you can never mistake a hidden salary for a free job. For India, skills and experienceText carry more signal than salary does.

The fast description is not always the complete one. Without fullDescription you get Naukri's search-result text: 72 to 4,579 characters in a 45-row sample, median 363, and one row held only 3.8% of what its job page showed. Turn fullDescription on and the same field runs to a median of 3,111 characters — an 8.6× lift — on a platform run that enriched 20 of 20. descriptionIsFull marks each row, so you always know which you got.

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How it works

Naukri renders its results in the browser from a JSON API that sits behind Akamai Bot Manager. This actor reads that API directly, so you get Naukri's own structured data rather than scraped HTML, and you never pay for a browser page load per job. A real browser is kept in reserve and takes over automatically if Naukri ever stops answering the fast path, so a change on Naukri's side costs speed, not your data.

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Pricing

Result	$0.30 / 1,000 — every job row
Full job details	$0.05 / 1,000 — only when fullDescription is on, and only for jobs actually enriched
Actor start	$0.002, once per run

Platform usage is included — you are not billed separately for compute. A run that returns nothing costs you only the start fee.

Leave fullDescription off and you pay $0.30/1,000. Turn it on and an enriched row — complete description, applicant count and view count included — is $0.35/1,000 all in. Jobs that come back without their detail fields are not charged the detail rate, so a page Naukri declines to serve costs you nothing extra.

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FAQ

Do I need a Naukri account or login? No. Everything here is public job-listing data.

How many jobs can I get from one search? Naukri caps each query's result set — a typical city+keyword search reports 11,000+ jobs. Use several locations, or narrow with daysOld, to reach further overall.

Can I get only remote jobs? Yes — set workMode to remote. Verified: every returned row's location reads Remote.

Why is salaryDisclosed false on most rows? Because most Indian employers hide the salary on Naukri. See the note above.

Can I schedule this? Yes. Use Apify Schedules, or the API, and filter with daysOld: 1 to pull only what was posted since your last run.

Does it work for all of India? Yes. Leave location blank for a nationwide search, or name any city — Bangalore, Mumbai, Delhi NCR, Hyderabad, Pune, Chennai, Kolkata, Noida, Gurgaon, Ahmedabad and the rest.

What if Naukri rate-limits my run? The run ends successfully with a status message explaining it, rather than failing — so a rate-limited minute never looks like a broken actor. Re-run shortly after.

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Limits

• Page size is fixed at 20 and must not be raised. Naukri treats its page-size parameter as advisory: it will cap a response to 20 rows while still advancing the offset by the number you asked for, so requesting 100 and getting 20 silently discards 80 jobs per page while the output looks perfectly healthy. This actor never does that.
• Naukri's own reported total is unreliable under the workMode filter — it reported 32,403 against an 11,276 baseline — so it is never used as a stopping condition.

Legal

This scrapes publicly visible job listings. It does not log in, bypass authentication, or collect candidate profiles or personal data. You are responsible for how you use the output, including under the GDPR and Naukri's terms.