Naukri Jobs Scraper — Listings, Salary & Skills Data

Scrape Naukri.com job listings with structured salary, skills, experience, work mode and company data. Search by keyword and Indian city, filter by experience, work mode and freshness, and export clean JSON/CSV — no code. Optionally pull full job descriptions with AmbitionBox salary benchmarks, benefits and applicant counts.

Built for recruiters, job-market analysts, and HR-tech teams who need reliable Naukri data with honest salary handling. Naukri hides the real pay on most postings — so when it's disclosed you get the exact figure (never a fake 0), and by enabling Add market salary you also get an AmbitionBox market-salary benchmark (marketAvgCtcLpa) for that role and company on every job.

What data can I extract from Naukri.com?

Every job returns a flat, single-record row. High-value fields:

Field	Description
title, companyName	Role and hiring company
salaryMinLpa, salaryMaxLpa, salaryDisclosed	Numeric salary in lakhs/annum — null + false when the employer hid it
marketAvgCtcLpa, marketMinCtcLpa, marketMaxCtcLpa	AmbitionBox market-pay benchmark for the role + company (enable Add market salary) — the salary signal even when Naukri hides the real number
experienceMinYears, experienceMaxYears, seniority	Experience band + a derived seniority level
skills	Skills/tags list
location, workMode	City and office / hybrid / remote
companyRating, companyReviewCount	AmbitionBox rating and review count
postedDate, jobUrl	Posting date and direct link

Turn on Add market salary (under Advanced) for the benchmark on every job — deduped by company+role and cached across runs. With Fetch full job descriptions on, each job also gets descriptionFull, keySkillsPreferred/keySkillsOther, roleCategory, industry, benefits, vacancy and applyCount (and the market benchmark comes bundled).

Turn on AI enrichment to also add an AI aiSummary, a distilled aiRequirements list, and a normalized aiSeniorityNormalized label per job — no API key of your own required.

Example output

{
  "jobId": "170426030208",
  "title": "Senior Data Scientist",
  "companyName": "Wipro",
  "companyRating": 3.6,
  "companyReviewCount": 66203,
  "salaryDisclosed": true,
  "salaryMinLpa": 27.5,
  "salaryMaxLpa": 42.5,
  "salaryLabel": "27.5-42.5 Lacs",
  "experienceMinYears": 14,
  "experienceMaxYears": 18,
  "experienceLabel": "14-18 Yrs",
  "seniority": "Senior",
  "location": "Pune",
  "workMode": "hybrid",
  "skills": ["Python", "Azure", "AI/ML", "LLM", "AWS"],
  "postedDate": "2026-06-23",
  "jobUrl": "https://www.naukri.com/job-listings-...-170426030208",
  "sourceKeyword": "data scientist",
  "sourceLocation": "pune"
}

When the employer hides the salary (most Naukri postings), the record stays honest — and with Add market salary on, it still carries a benchmark:

{ "title": "Python Developer", "companyName": "Persistent", "salaryDisclosed": false, "salaryMinLpa": null, "salaryMaxLpa": null, "salaryLabel": null, "marketAvgCtcLpa": 22.5, "marketMinCtcLpa": 18, "marketMaxCtcLpa": 30 }

How to use the Naukri scraper (quick start)

1. Enter one or more Job keywords (e.g. data scientist, java developer).
2. Optionally add Cities (e.g. bangalore, mumbai) — leave empty to search all of India.
3. Set Max jobs and, if you like, Experience, Work mode, or Posted within.
4. Run it. Download results as JSON, CSV, or Excel, or pull them via the API.

Minimal input:

{ "keywords": ["data scientist"], "locations": ["bangalore"], "maxJobs": 200 }

Recruiter input with full descriptions and market pay:

{
  "keywords": ["backend engineer"],
  "locations": ["bangalore", "hyderabad"],
  "experienceYears": "5",
  "workMode": ["hybrid", "remote"],
  "fetchFullDescription": true,
  "maxJobs": 500
}

How much does it cost to scrape Naukri.com?

This actor uses pay-per-result — you only pay for the jobs you actually get. See the pricing shown above for the exact rate. Base listings are the cheapest; full descriptions and AI enrichment are optional and billed separately, so you never pay for extras you don't use.

Who is this Naukri scraper for?

• Recruiters & staffing — pull roles by skill + city + experience to map who's hiring and at what pay.
• Job-market & HR analysts — track hiring volume, salary bands and in-demand skills by role, city and company over time (schedule it with Only new jobs).
• Compensation research — combine disclosed salaries with AmbitionBox market benchmarks to build pay ranges by role and seniority.
• Job boards & aggregators — ingest fresh Indian job supply with clean, structured fields.
• AI / RAG builders — feed structured job data (optionally AI-summarized) into search, matching or analytics products.

Can I filter jobs and monitor new postings?

Yes. Filter by experience, work mode (office/hybrid/remote) and posting freshness, or paste full Naukri search-result URLs under Advanced to scrape exactly the filtered searches you build on the site. Turn on Only new jobs and schedule the actor to receive just the postings added since your last run — ideal for daily monitoring.

Frequently asked questions

Is it legal to scrape Naukri.com?

This actor collects publicly available commercial job postings (no logins, no personal candidate data). You are responsible for using the data in line with Naukri's terms and applicable laws. It is designed for market research, recruitment and analytics use cases.

Does it handle hidden salaries?

Yes — honestly, and it can still give you a salary signal. Naukri hides the real pay on most postings; when that happens salaryDisclosed is false and the disclosed figures are null (never a fake 0). Enable Add market salary and every job also carries an AmbitionBox market-salary benchmark (marketAvgCtcLpa plus a typical min/max) for that role at that company — the honest way to get pay data from Naukri. It's deduped by company+role and cached across runs to keep it cheap.

How many jobs can I scrape per search?

A single keyword+city search paginates through Naukri's results; to go wide, add multiple keywords and cities — the actor fans out across every combination and de-duplicates jobs automatically.

What's the salary format?

Salaries are normalized to LPA (lakhs per annum) as numeric salaryMinLpa / salaryMaxLpa, with the original label preserved in salaryLabel.

Do I need a proxy?

Yes — Naukri is protected by Akamai. The actor uses Apify residential proxies (India by default) to mint a valid session and rotate on blocks. This is preconfigured; you don't need to set anything up.

Can I get the full job description?

Turn on Fetch full job descriptions to add the complete description plus AmbitionBox salary benchmarks, benefits, education and applicant counts to every job.

Can I get an AI summary of each job?

Yes — turn on AI enrichment to add a short aiSummary, a distilled aiRequirements list, and a normalized seniority label to every job. It uses a low-cost model, needs no API key of your own, and is billed at the AI rate.

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Support

Found a bug or need a field added? Open an issue on the Issues tab and we'll take a look.