Naukri Scraper: India Job Listings, Salaries and Full Descriptions

Naukri Scraper turns Naukri.com, India's largest job board, into clean structured data. Search by keyword and city, or paste job and search links straight from the site, and every hit carries the title, company, skills, experience band, salary and posting date from the search results. Turn on full job details and the same record also carries the complete description, key skills, education, employment type, industry, company profile and view/apply counts from the job's own page. Export to JSON, CSV or Excel, or pull results straight into your app through the API.

Why This Scraper?

• Two ways to find jobs. Search by keyword and an optional city, or paste your own job or search links, filters and all.
• Every filter you built on the site comes along. A pasted search link keeps the filters you applied on naukri.com, because the page path carries them; the actor walks it exactly as configured.
• Card fields plus full detail on demand. Every hit carries the search-card fields; switch on Fetch full job details for the complete description, key skills, education, employment type, industry, company profile and view/apply counts, and pay the detail surcharge only for records whose job page read actually succeeded.
• Built for schedules. Incremental mode returns only new, updated and reappeared postings on recurring runs, and a posting is only marked expired once a run has genuinely scanned the whole tracked search end to end.
• Resume without repaying. Continue one interrupted run from its previous run or dataset id and skip everything already collected there.
• A refused run fails loudly instead of returning an empty dataset, so "no jobs matched" is never confused with "the site could not be read".
• Send results straight into your apps. Pipe finished runs into Notion, Linear, Airtable or your own MCP-connected tool.

Use Cases

• Recruiters and staffing agencies: track fresh postings for specific roles and cities without checking the site by hand.
• Job seekers and career sites: build a personal or aggregated feed of matching openings with salary, experience band and posting date.
• Compensation and market research teams: collect salary bands, experience ranges and skill tags across postings to benchmark a role or region.
• Competitive intelligence teams: monitor a set of roles or companies and get notified the moment a new or changed posting appears, using incremental mode.
• Data teams and ML pipelines: build historical datasets of postings, skill demand and hiring activity for analysis.

Data You Get

Sample shape: values are illustrative placeholders, not from a live record.

Field	Example
recordId / jobId / kind	"999000111222" / "999000111222" / "job"
title	"Senior Backend Engineer"
url	Naukri link back to the job's own page
companyName	"Example Tech Solutions Pvt Ltd"
companyId	500123
companyLogo	Naukri-hosted logo image link
skills	["Python", "Django", "SQL"]
experience / minimumExperience / maximumExperience	"3-6 Yrs" / 3 / 6
salary / currency	"8-14 Lacs PA" (the site's own salary label; the numbers are in salaryDetail) / "INR"
salaryDetail	{ "minimumSalary": 800000, "maximumSalary": 1400000, "currency": "INR", "hideSalary": false, "variablePercentage": 10 }
location	"Bengaluru"
descriptionSnippet	short excerpt shown on the search card
vacancy	2
postedAt	"2026-06-15T00:00:00+00:00" (the exact posting timestamp)
postedDaysAgoLabel	"3 Days Ago" (a volatile display label, not the reliable field)
walkinJob	false
searchScope	the keyword and city, or pasted link, that produced this row
companyRating	{ "aggregateRating": 4.2, "reviewsCount": 350, "reviewsUrl": "..." }
groupId / isTopGroup / companyJobsUrl	the employer's company group id (the id topCompanies accepts), whether it is a featured top employer, and its careers page on the site
externalApply / applyUrl / listingSource	true and the employer's own application link when applying happens off-site; listingSource is how the listing reached the site (jp posted on the site, crawled copied from the employer's careers site)
diversityTags	["women", "women returning to work"] when the employer flags a hiring preference
workFromHomeType / keySkills	"Hybrid", "Remote" or "Work from office" / { "preferred": [...], "other": [...] } (full details)
walkInDetails	walk-in jobs only: { "startDate": "2026-10-05", "endDate": "2026-10-06", "dailyTiming": "10.00 AM - 4.00 PM", "venueAddress": "...", "saturdayWorking": true, "sundayWorking": true } plus mapUrl / contactName / contactPhone when the employer publishes them
internshipDuration	internships only: "3 months duration" (the stipend is in salary, e.g. "15,000/month")
roleCategoryId / hasApplyQuestionnaire / scrapedAt	the site's numeric role category id / true when applying asks the employer's screening questions / when this row was collected

With Fetch full job details on, each record also carries description, locations, locationDetails (each location with its localities and location page link), locationIds (the site's numeric city ids, usable in the cities filter), education, educationDetails (ug / pg / ppg lists), employmentType, jobType, industry, functionalArea, jobRole, roleCategory, postedByConsultant, viewCount, applyCount, companyDetails (name, description, address, website, hiring-for and overview link, each only when the job page serves it), companyBenefitsUrl and companyBenefitsReportedBy from the job's own page, plus a structured salaryDetail breakdown whenever the card or job page carries one. The description comes in three formats: description (plain text), descriptionHtml (the job page's own markup) and descriptionMarkdown (ready for LLM and Markdown pipelines). In Incremental mode, each record also carries changeType, changedFields, firstSeenAt, lastSeenAt and isRepost (plus repostOfJobId when a new job id re-posts a job the campaign already tracked).

Output views

The Output tab offers six table views of the same dataset: Jobs (every field), Job details (the job-page fields), Company insights (AmbitionBox) (rating, salary insight, benefits, company profile), Company reviews (one row per review snippet, with its job), Walk-in interviews (walk-in dates, timing and venue) and Changes (incremental mode) (change type, changed fields, first/last seen, reposts). Reviews always ride on their job row in the dataset itself.

The Run summary link on the same tab opens a small OUTPUT record in the run's key-value store: mode, recordsEmitted, per-search scopes, scopesFailed, pagesRejected, maxItemsReached (true only when the item limit was actually reached), pageLimitReached (true when the page limit stopped a search), coverageShortfall (a search the source said had more jobs than were served), unresolvedFilterValues (filter names or ids that could not be matched, first 20) and finishedAt.

How to Use

1. Pick a mode: search (keywords, optionally with one city) or url (paste job or search page links).
2. Fill in the keywords and city, or the links, and turn on Fetch full job details if you want the full description and company profile.
3. Set Max items (and optionally Max pages per search) to control run size and cost, then click Start.
4. Download the dataset as JSON, CSV or Excel, or read it through the API.

Search two keywords in one city:

{
  "mode": "search",
  "keywords": ["python developer", "data analyst"],
  "location": "bangalore",
  "fetchDetails": true,
  "maxItems": 50
}

Paste a filtered search link:

{
  "mode": "url",
  "urls": ["https://www.naukri.com/python-developer-jobs-in-bangalore"],
  "fetchDetails": true
}

Card-only run, capped by pages instead of items:

{
  "mode": "search",
  "keywords": ["sales executive"],
  "fetchDetails": false,
  "maxPages": 5,
  "maxItems": 0
}

Paste a single job link:

{
  "mode": "url",
  "urls": ["https://www.naukri.com/job-listings-senior-backend-engineer-example-tech-solutions-bengaluru-999000111222"]
}

URL mode: every supported link shape

In URL mode the Job or search page links field ships with a default list of eight distinct examples (one per genuinely different shape: keyword search, keyword plus city, city only, category, company careers, city-scoped company careers, company overview, single job page), so an untouched URL-mode run scrapes one page set per shape. The prefill adds a few variants of those shapes (page 2, a filter query, tracking parameters, the mobile host, the bare host) that resolve to the same targets. A run with the list emptied and no job ids ends as failed with a "No input" message. Search filters apply to Search mode only; a pasted search link keeps the filters in its own address.

Paste any mix of these into Job or search page links; search and company links are walked forward page by page the same way a Search-mode run is. m.naukri.com and the bare naukri.com host (no www) both work for every shape below, since the site itself redirects them.

Shape	Example	What it does
Keyword search	naukri.com/python-developer-jobs	Walks the keyword search
Keyword + city	naukri.com/python-developer-jobs-in-bangalore	Walks the keyword search in that city
City only, no keyword	naukri.com/jobs-in-bangalore	Walks every job in that city
A specific page	naukri.com/python-developer-jobs-2	Starts the walk from page 2 (treated as a partial scope for Incremental mode's EXPIRED detection)
A filtered link you built on the site	naukri.com/python-developer-jobs?experience=5	Keeps every filter from the URL's query string
Category pages	/fresher-jobs, /walkin-jobs, /internship-jobs, /work-from-home-jobs, /it-jobs	Each walks that fixed category
Company careers page	naukri.com/tata-technologies-jobs-careers-1218	Walks that one employer's open jobs only
Company careers page in one city	naukri.com/capgemini-jobs-careers-in-bengaluru-gid-1288	Walks that employer's open jobs in that city
Company overview page	naukri.com/capgemini-overview-1288 (every record's companyDetails.overviewUrl)	Walks every open job of that company group
A single job page	naukri.com/job-listings-...-<jobId>	Reads that one job directly (no search)
A job page with tracking params	naukri.com/job-listings-...-<jobId>?src=...&sid=...	Tracking params are ignored; the job still resolves by its numeric id

Naukri resolves a job page purely by the numeric id at the end of the URL; the surrounding slug text is cosmetic, so even a mismatched or garbled slug still reads the right job as long as the id is correct.

Any other naukri.com link, such as a recruiter page (/recruiters/...) or a jobseeker-login-only page (/mnjuser/...), has no public job data to scrape and is skipped with a warning in the run log rather than silently dropped.

Run it from your code

Python:

from apify_client import ApifyClient

client = ApifyClient("<YOUR_APIFY_TOKEN>")
run = client.actor("abotapi/naukri-com-scraper").call(run_input={
    "keywords": ["python developer"], "location": "bangalore"
})
for job in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(job["title"], job["companyName"], job["salary"])

JavaScript:

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: '<YOUR_APIFY_TOKEN>' });
const run = await client.actor('abotapi/naukri-com-scraper').call({
  keywords: ['python developer'], location: 'bangalore',
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();

Or connect it to Make, Zapier, n8n, Google Sheets or webhooks from the Integrations tab.

Caps and page size

The source serves 20 jobs per page; the actor respects that page size and treats a short page as the natural end of a search. Max items is the one cap that always applies (a total across every keyword or link, 0 for unlimited); Max pages per search additionally bounds how deep any single keyword or search link is walked. When the source reports more matching jobs than the walk actually served, the affected search is treated as incomplete rather than assumed finished.

If job page reads keep failing, the actor stops reading job pages and returns search-card data for the rest of the run, without the detail charge for those rows. Currently a single job page that fails all three of its read attempts is enough to switch this on, so an otherwise healthy run can return its later rows without full details; re-run the search if you need them.

Resume & recurring updates

• Resume (resumeFromRunId) continues one interrupted run: paste its run or dataset id and the actor skips every record id already collected there, so you don't pay twice. It is unrelated to the page-by-page walk itself, which always restarts from page one and stops on its own natural end for the current run.
• Incremental mode (incrementalMode) is for repeating the same search on a schedule. Each record is classified NEW, UPDATED (with changedFields), UNCHANGED (suppressed and not billed unless emitUnchanged is on), REAPPEARED or EXPIRED (only after a run that scanned the whole tracked search, and only with emitExpired). stateKey names or shares the stored state; leaving it empty derives one automatically from the search and filter settings (never from Max items or Max pages, so raising a cap keeps the same baseline). With incremental mode off, output is exactly as before. A day-count age label re-rendering on its own (for example "13 Days Ago" becoming "14 Days Ago") never counts as an update; the exact posting timestamp does. The view/apply counts, the AmbitionBox rating block, the AmbitionBox review snippets, the AmbitionBox salary insight's figures, the company logo URL and the search label are ignored the same way by default, since each drifts on its own without the posting itself changing. companyBenefits is NOT ignored by default: it changes about as rarely as the posting itself, so a real change there is treated as a real update.
• Skip reposted jobs (incremental mode only) (skipReposts): every incremental row carries isRepost; it is true when a NEW job id re-posts a job this campaign already tracked under another id (same title, employer and location, repostOfJobId names the earlier id). Turn this on to leave those reposts out (not returned, not billed, still remembered).
• Ignore fields when detecting changes (incremental mode only) (ignoreFieldsForChanges) extends that default ignore list with your own field names, for example salary if a currency re-tagging alone shouldn't count as an update. Dotted paths like companyRating.aggregateRating reach into a nested field without ignoring its siblings. Ignored fields are still returned in the output; they just don't drive the NEW/UPDATED/UNCHANGED decision.

Send results into your apps (MCP connectors)

Optionally pipe the scraped results into the apps you already use, via Model Context Protocol (MCP) connectors. This is an extra delivery step after the scrape: the Apify dataset is never changed.

What gets written to the connector: a condensed, human-readable summary of each record, not the full JSON. Each item becomes one entry with a title and its key fields flattened to plain text. The complete record always stays in the Apify dataset.

1. Authorize a connector once under Apify > Settings > Integrations (Notion, Linear, Airtable, or Apify).
2. Select it in the "MCP connectors" input field. (If the picker is empty, you haven't authorized a connector yet.)
3. For Notion, also set notionParentPageUrl to the page where items should be created.

The connection is mediated by Apify's MCP proxy, so this actor never sees your third-party credentials. Leave the field empty to skip.

Input Parameters

Parameter	Type	Default	Description
mode	string	search	search (walk keyword results) or url (read pasted links).
keywords	array	["python developer"]	Job keywords for search mode, exactly as typed into the site's search box.
location	string	(none)	Optional city applied to every keyword above. Leave empty to search all India.
sortBy	string	relevance	Search mode: relevance (site default) or date (newest first).
experience	integer	(none)	Search mode: only jobs open to this many years of experience (0-30, 0 = fresher).
freshness	string	any	Search mode: only jobs posted within 1, 3, 7, 15 or 30 days.
workMode	array	(none)	Search mode: any of office, remote, hybrid, temporary_wfh.
salaryRange	array	(none)	Search mode: any of the site's salary bands in lakhs per year, 0to3 up to 100to500 (1-5 crore).
cities	array	(none)	Search mode: city names (e.g. Hyderabad, Bangalore) or numeric city ids; several at once.
department	array	(none)	Search mode: department names as the site shows them (e.g. Data Science & Analytics) or ids.
roleCategory	array	(none)	Search mode: role category names (e.g. Software Development) or ids.
industry	array	(none)	Search mode: industry names (e.g. IT Services & Consulting) or ids.
companyType	array	(none)	Search mode: any of foreign_mnc, corporate, indian_mnc, startup, govt_psu, mnc, others.
postedBy	string	any	Search mode: company (direct employer) or consultant (recruitment agency) only.
topCompanies	array	(none)	Search mode: company names (e.g. Infosys) or numeric company group ids.
walkInOnly	boolean	false	Search mode: only walk-in interview jobs.
stipend	array	(none)	Search mode, internship searches: any of unpaid, 0to10k, 10to20k, 20to30k, 30to40k, 40to50k, 50k_plus per month.
internshipDuration	array	(none)	Search mode, internship searches: any of 1 to 6 months or flexible.
ugCourse	array	(none)	Search mode: accepted undergraduate qualifications by name (e.g. B.Tech / B.E., B.Sc) or id.
pgCourse	array	(none)	Search mode: accepted postgraduate qualifications by name (e.g. MCA, M.Tech) or id.
urlParams	array	(none)	Advanced: extra query parameters added as-is to every search page address, for a site filter not listed above.
urls	array	sample	Job or search page links for URL mode.
jobIds	array	(none)	Job ids (the 12-digit number ending a job link) or job links, read directly, in either mode.
fetchDetails	boolean	true	Read each job's own page for the full detail set. Adds the per-job detail surcharge.
maxItems	integer	20	Total record cap across all keywords or links. 0 means unlimited.
maxPages	integer	0	Result pages walked per keyword or search link. 0 means no page limit.
maxReviewsPerJob	integer	20	Caps how many AmbitionBox employee-review snippets are kept per job, when the job's own page serves them. Only applies when Fetch full job details is on.
proxyConfiguration	object	Apify Proxy	Connection settings; the standard shared pool by default.
resumeFromRunId	string	(none)	Continue one specific interrupted run or dataset without re-collecting what it already gathered.
incrementalMode	boolean	false	Turn on for recurring runs over the same search: return only new, updated and reappeared records.
stateKey	string	(none)	Name or share an incremental-mode monitoring campaign.
emitUnchanged	boolean	false	Also return (and bill) records that have not changed since the last run.
emitExpired	boolean	false	Also return (and bill) records no longer found, once a run has fully scanned the tracked search.
skipReposts	boolean	false	Incremental mode only: leave out new job ids that re-post a job the campaign already tracked (same title, employer and location).
ignoreFieldsForChanges	array	(none)	Incremental mode only: extra field names (or dotted paths) that should not make a record count as UPDATED. The age label, view/apply counts, the AmbitionBox rating block, the company logo URL and the search label are already ignored by default.
mcpConnectors	array	(none)	Optional: send a summary of each record to apps you authorized under Integrations.
notionParentPageUrl	string	(none)	Notion connector only: page under which records are created.
maxNotifyListings	integer	50	Cap on records exported to each connector per run.

Output Example

Sample shape: values are illustrative placeholders, not from a live record.

{
  "recordId": "999000111222",
  "jobId": "999000111222",
  "kind": "job",
  "title": "Senior Backend Engineer",
  "url": "https://www.naukri.com/job-listings-senior-backend-engineer-example-tech-solutions-bengaluru-999000111222",
  "companyName": "Example Tech Solutions Pvt Ltd",
  "companyId": 500123,
  "companyLogo": "https://img.example.com/logo_images/groups/v1/500123.gif",
  "skills": ["Python", "Django", "SQL"],
  "experience": "3-6 Yrs",
  "minimumExperience": 3,
  "maximumExperience": 6,
  "salary": "8-14 Lacs PA",
  "salaryDetail": { "minimumSalary": 800000, "maximumSalary": 1400000, "currency": "INR", "hideSalary": false },
  "location": "Bengaluru",
  "descriptionSnippet": "Own backend services for a growing product team...",
  "description": "Full job description text goes here...",
  "vacancy": 2,
  "postedAt": "2026-06-15T00:00:00+00:00",
  "postedDaysAgoLabel": "3 Days Ago",
  "currency": "INR",
  "walkinJob": false,
  "searchScope": "python developer in bangalore",
  "education": "Any Graduate",
  "employmentType": "Full Time, Permanent",
  "jobType": "fulltime",
  "industry": "IT Services",
  "functionalArea": "Engineering - Software",
  "companyRating": { "aggregateRating": 4.2, "reviewsCount": 350 },
  "companyReviews": [
    {
      "reviewerName": "Anonymous",
      "roleAndLocation": "Backend Engineer in Bengaluru",
      "rating": "4",
      "likes": "Good work-life balance and a supportive team.",
      "dislikes": "Promotions could be faster.",
      "publishedOn": "01 Feb 2026",
      "reviewUrl": "https://www.ambitionbox.com/reviews/example-tech-solutions-reviews?rid=1234567"
    }
  ],
  "companySalaryInsight": {
    "jobProfileName": "Senior Backend Engineer",
    "averageCtc": "14.2",
    "minCtc": "11.0",
    "maxCtc": "18.5",
    "salariesUrl": "https://www.ambitionbox.com/salaries/example-tech-solutions-salaries/senior-backend-engineer"
  },
  "companyBenefits": ["Health Insurance", "Free Meal", "Transport / Travel Support"],
  "descriptionMarkdown": "**About the role**\n\n- Own backend services\n- Mentor two engineers",
  "roleCategoryId": "1028",
  "hasApplyQuestionnaire": false,
  "scrapedAt": "2026-06-18T09:30:00+00:00"
}

companyReviews, companySalaryInsight and companyBenefits come from the AmbitionBox widget naukri.com's own job page embeds (not a separate ambitionbox.com request); they're only present when Fetch full job details is on and the source actually served that widget for the company. maxReviewsPerJob caps the review list; the source itself may serve fewer than the cap.

Plan Requirement

The actor runs on Apify's pay-per-event pricing: one event when the run starts, one event per job record returned, and one job detail enrichment event per record when Fetch full job details is on and the job page read actually succeeded. Company review snippets ride on their job row and have no event of their own. The Pricing tab shows the live rates.

Proxy: the default Apify Proxy setting reads the site on a measured basis (the standard shared pool served full 20-job result pages in testing), so most runs need no action. Free Apify plans do not include residential proxies. If the default connection is refused, the actor tries the next connection on its own and logs which one served the data. If your runs are still refused, pick Apify residential (India) under Connection & proxy (billed per GB on your account), or supply your own proxy URLs. When nothing could be loaded the run ends as failed with one of these messages: "The proxy connection was refused for this account, so no page could be read. Your Apify plan does not include proxy access; a paid plan is required", "No results: residential proxies are unavailable on this run (Apify free plans do not include them), and the backup connection could not load the requested Naukri.com pages", or "Could not load any results page (the requests failed), so nothing was collected. This is a connection problem, not an empty search."

FAQ

How much does it cost?

You pay per job record returned, plus one detail enrichment charge per record when Fetch full job details succeeds for it. The Pricing tab shows the current rates. Use Max items to cap the cost of any run.

Is it legal to scrape Naukri.com?

This actor collects only publicly available job listing data. You are responsible for how you use it: follow Naukri's terms and the laws that apply to you, and get legal advice if you plan commercial redistribution.

Can I get only new job postings on a schedule?

Yes. Schedule the actor from the Schedules tab and turn on Incremental changes for scheduled runs. Later runs then return only new, updated and reappeared postings, and unchanged ones are suppressed and not billed unless you turn on Emit unchanged.

Why didn't I get any EXPIRED rows even with Emit expired on?

Expired postings are only produced once a run has scanned its whole tracked search end to end: not capped by Max items or Max pages, not resumed, every scope reached its natural end (including a scope whose very first page comes back empty while the source still reports matching jobs for it, which also counts as incomplete), and the source's own reported job count matched what the walk actually served. A pasted search link that already starts past page one, or carries its own filter query string, counts the same way: the run never saw that scope's full window, so it is not trusted to decide what is EXPIRED from it. This check applies to the whole run, not one keyword at a time, so for example a two-keyword incremental run where the first keyword finishes cleanly but the second hits Max items mid-page skips expiry detection for both keywords that run. Raise Max items (or set it to 0), or give each keyword its own scheduled run and state key, so a cap on one search never withholds expired detection on another.

What's the difference between Resume and Incremental mode?

Resume (resumeFromRunId) continues ONE specific interrupted run: paste its run or dataset id and the actor skips everything it already collected there. Incremental mode is for running the SAME search again and again, for example daily, and getting only what changed; it keeps its own state per search and filter combination, or per State key.

Why did my run fail instead of returning an empty dataset?

The log may show a boxed warning "The selected connection is unavailable to this run. Apify free plans do not include residential proxies. Continuing on a backup connection; some pages may still be unavailable." and, once a backup connection serves data, "Served over the backup connection (the default connection was unavailable)." Both are informational; the run keeps going.

If every page read is refused, the run stops with a clear message so "no jobs matched" is never confused with "the site could not be read". Run it again in a few minutes. If only some keywords or links could be read, you still get what was found from the rest. One exception in Incremental mode: the check counts only returned records, so a scheduled run where every posting read was unchanged (and suppressed) and one page was refused also ends as failed, even though its state was still updated. Re-run it, or turn on Emit unchanged (which returns and bills those rows) if you need such runs to succeed.

Can I use it with AI agents or MCP?

Yes. Call it from any Apify integration or MCP client, and use the connector field to push results into Notion, Linear or Airtable as the run finishes.

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