Naukri Jobs Scraper — India's #1 Job Board | PPE

Scrape job listings from Naukri.com — India's #1 job board with 70+ million registered jobseekers and millions of active job postings across every industry and skill category.

Features

• Search by keyword and location — enter any job title, skill, or role (e.g. python developer, data analyst, product manager) and optionally filter by city or region.
• Multiple keywords — supply a list; each keyword is scraped independently in sequence.
• Paginated results — configure how many pages to fetch per keyword (each page returns 20 jobs).
• Rich structured output — every job record includes: job ID, title, company, location, experience range, salary (when disclosed), skills list, posted date, direct job URL, and a clean description snippet.
• No login required — uses the public Naukri v2 internal API; no Naukri account needed.
• Pay per job delivered — PPE pricing, you only pay for actual results.

How to Use

1. Open the actor in Apify Store and click Try for free.
2. Set searchKeywords — a list of job titles or skills (e.g. ["data engineer", "machine learning engineer"]).
3. Set location — city or region filter (e.g. Bangalore, Mumbai, india). Leave as india for all-India results.
4. Adjust maxItems and maxPages to control output volume.
5. Leave the proxy on the default Apify RESIDENTIAL group with country IN (India) — this is required for reliable access to Naukri.
6. Click Start and collect results from the Dataset tab.

Input Example

{
  "searchKeywords": ["python developer", "data analyst"],
  "location": "Bangalore",
  "maxItems": 200,
  "maxPages": 10,
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": ["RESIDENTIAL"]
  }
}

Output Example

Each item in the dataset looks like this:

{
  "job_id": "050626924194",
  "title": "Python Developer with GenAI",
  "company": "Infosys",
  "location": "Bengaluru",
  "experience": "2-3 years",
  "salary": null,
  "skills": ["python", "rest", "api development", "django", "llm", "aws", "gcp"],
  "posted_date": "2026-06-05",
  "job_url": "https://www.naukri.com/job-listings-python-developer-with-genai-infosys-bengaluru-2-to-3-years-050626924194",
  "description_snippet": "Bachelor of Engineering. Strong Python skills required. Experience with LLMs and cloud platforms…",
  "employment_type": "Full Time, Permanent",
  "role": null,
  "keyword_query": "python developer",
  "scraped_at": "2026-06-07T10:00:00Z"
}

Pricing

This actor uses pay-per-event (PPE) billing: you are charged per job record delivered to the dataset.

• $2.00 per 1,000 jobs (i.e., $0.002 per job).
• Example: scraping 500 Python developer jobs in Bangalore = ~$1.00.
• Example: scraping 5,000 data analyst jobs across India = ~$10.00.
• Compute costs (Apify platform usage, proxy) are charged separately on your Apify account.

Use Cases

• Talent market research — track which companies are hiring, for what roles, at what experience levels.
• Salary benchmarking — aggregate disclosed salary ranges by role and location.
• Skills demand analysis — identify trending skills keywords across thousands of active job postings.
• Competitive intelligence — monitor competitor hiring activity in specific regions or tech stacks.
• Lead generation — find companies actively hiring in your target market.

FAQ

Does it require a Naukri account? No. The scraper uses Naukri's public-facing API. No login, no account, no credentials needed from you.

How many results can I get per keyword? Naukri typically returns 20 jobs per page. With maxPages=100, that's up to 2,000 jobs per keyword. Naukri declares total result counts in the API response; pagination stops automatically when all results are exhausted.

Why do some jobs have salary: null? Naukri allows companies to hide salary information. When a company marks salary as "not disclosed," the field is null. This is very common on Naukri — typically 60–80% of listings hide salary.

Is this legal? This actor scrapes publicly visible job listings only — the same data any anonymous visitor sees on Naukri.com. No authentication is required, no private data is accessed. Use of this data is subject to Naukri's Terms of Service and applicable laws in your jurisdiction. The actor is intended for research, analysis, and legitimate business intelligence purposes.

What proxy group should I use? Keep the default: Apify RESIDENTIAL group with country IN (India). Naukri only lets India-based residential IPs through reliably to the public job API, so this is the configuration the actor is built and tested for. Proxy costs are billed to your Apify account at Apify's standard rates.

More scrapers from our toolkit

Building a data pipeline? These actors pair well with this one — each runs on your own Apify account with the same pay-per-result pricing, no subscription:

• Seek Jobs Scraper
• Stepstone Jobs Scraper
• Workable Job Scraper
• Xing Jobs Scraper
• Ashby Job Scraper
• Dice Jobs Scraper

Chain any of them together from the Integrations tab (the Run succeeded trigger) to build a multi-step workflow — one actor's output feeds the next.

Usage statistics

This Actor creates a small, content-free summary at the end of each run. It is used only to monitor reliability and improve this Actor. A copy is saved as USAGE_STATS in your own Apify key-value store, so you can see the exact record created for your run.

Set disableUsageStats to true in the input to opt out. Nothing is sent then; your USAGE_STATS record only says that statistics were disabled.

Only these fields are recorded:

• schema version, Actor name and build number;
• UTC start and finish hour (not a precise timestamp);
• run duration, number of results and time to the first result, each as a coarse range;
• whether the result was empty, the end status, and an error type from a fixed list;
• memory setting and counts of charged events;
• names of the input fields you set, never their values;
• the selected option for input fields that offer a fixed list of choices (for example a sort order).

We do not collect input text, search terms, URLs, domains, usernames, email addresses, names, proxy credentials, tokens, scraped records, output items, raw error messages, stack traces, or hashes of any of those values. Records are kept for no longer than 13 months, used only as aggregated operational statistics, and never sold or shared.

Additional fields (Phase 2)

This Actor also records your Apify user ID, whether Apify marks the account as paying, the size range of list inputs, the selected country when the input offers a fixed list of countries, and one category from a fixed Actor taxonomy. We use these fields only for aggregate reliability, repeat-use and cross-Actor analysis; reports suppress any cell with fewer than five distinct users.

The same disableUsageStats: true input flag turns these fields off too. The user ID is removed after 13 months; we do not export, sell, share, or attempt to re-identify this data.

Run-outcome signals (v2)

To learn whether a run did what it was asked to do, the record also holds a few more coarse ranges and yes/no flags. None of them contains content:

• the result limit you asked for (a range, when the input has one) and what share of it was delivered;
• results delivered per input item you listed (a range);
• output quality as ranges: how fully the result fields were filled, the share of rows that look like errors, the share of duplicate rows, and how many different fields appeared. These are counted in memory while results are saved; no result content is kept;
• how the run was started (console, API, schedule, webhook, another Actor);
• how it ended: stopped by you, timed out, reached the requested limit, stopped by the charge limit, and how many times the platform moved the run;
• if this Actor reports it: how many items to process worked or failed (ranges) and one failure reason from a fixed list;
• a short code made from the names of the input fields you set, never their values.

Repeat-run fingerprint (v2)

When your Apify user ID is recorded (see above), the record also holds an 8-character one-way code made from your input (proxy settings left out) and this Actor's name. It only lets us see that the same account ran the same input again soon after an unsatisfying run; we never see the input itself. It is stored only in the database, never published, and reports use it in aggregate with the same five-user minimum. It is the one exception to the statement above that no hashes are collected, and disableUsageStats: true turns it off.