Naukri Jobs Scraper

🔎 What does Naukri Jobs Scraper do?

Naukri Jobs Scraper collects public job listings from the main Naukri India site. Enter job titles, skills, company names, and optional Indian locations. The Actor returns clean job rows with descriptions, skills, salary, experience, company data, posting data, and canonical Naukri job URLs.

The default dataset grain is one row per unique Naukri job listing observed in one Actor run. The Actor uses the Naukri jobId to remove overlap between keywords, locations, and pages.

The Actor uses logged-out public data. It does not need a Naukri account, cookies, or an API key. It does not access candidate profiles, submit job applications, or solve CAPTCHAs.

✅ Clean data with clear controls

The Actor focuses on clean rows, easy input, useful fields, and less manual search work.

• Clear India scope: The Actor covers the main Naukri India site. It does not cover NaukriGulf.
• Direct search input: Enter keywords, locations, posting age, experience, and sort order. The Actor has no start URL input or hidden location IDs.
• Useful filters: Search by job title, skill, company, location, posting age, and experience. You can also exclude company names.
• Firm result cap: When you set maxItems, the Actor never saves more than this number. It can save fewer rows. OUTPUT states why. Omit maxItems from API input when you do not want a saved-row limit.
• Clean structured rows: Each saved job uses 30 named public fields. The row includes a company rating and review count when Naukri makes them public. It does not include large company-review records that add cleanup work.
• Clear price: The price is exactly $0.00125 per saved unique job. Duplicate candidates, filtered candidates, and empty searches do not cause a result charge.
• Easy first run: Use the Apify form or API. You do not need a Naukri login, cookies, or a Naukri API key.

With Naukri Jobs Scraper, you can:

• 🔎 Search jobs by title, skill, company, and Indian location.
• 📝 Collect public job descriptions and skills in the base row.
• 💰 Extract source salary text and conservative numeric salary ranges.
• 🪜 Extract source experience text and numeric experience ranges.
• ♻️ Save one row per Naukri job ID.
• ⚖️ Spread coverage across keyword and location search pairs.
• 📊 Check candidates, duplicates, filters, source states, and stop reasons.
• 📦 Export rows as JSON, JSONL, CSV, Excel, XML, RSS, or HTML.

📦 What Naukri job data can I extract?

Each default dataset row represents one unique public Naukri job listing observed in the run.

Data group	Example fields
🆔 Job identity	jobId, jobUrl, schemaVersion
💼 Job details	title, descriptionText, skills
🏢 Company	companyName, companyLogoUrl, companyRating, companyReviewCount
📍 Location	location
🪜 Experience	experienceRaw, experienceMinYears, experienceMaxYears
💰 Salary	salaryRaw, salaryMin, salaryMax, salaryCurrency, salaryPeriod
📅 Time	postedAt, postedAtRaw, observedAt
🔍 Search context	searchTerm, searchLocation, sourceUrl, pageNumber, rankOnPage
🚦 Row state	status, statusReason, source

Missing public values stay null. The Actor does not replace missing salary, experience, rating, description, or posting data with zero.

🧱 Data model and row grain

The Actor keeps two output shapes separate.

Output	Model shape	One record means	Identity or scope
Default dataset	Job observation fact	One Naukri job observed in one run	jobId within the run
OUTPUT record	Run state	One completed Actor run	Current Actor run

observedAt records when the run observed the job. The same jobId can appear again in a later run. This behavior lets you build job snapshots over time.

The public row is flat for CSV, spreadsheets, APIs, and warehouse loads. skills is the only multi-value field. If you load the data into a relational warehouse, you can place skills in a job-to-skill bridge table. A bridge table stores a many-to-many relationship without copying the job measures.

The internal sequence is:

buyer input
-> keyword and location search pairs
-> public search candidates
-> normalized job observation
-> company filter
-> jobId duplicate check
-> optional saved-row limit and charge limit
-> dataset row and result charge
-> OUTPUT run state

🔄 Input to output seam

The input to output seam is the point where buyer settings and source evidence become stable public fields. It keeps selection settings separate from observed job facts.

Public input	Internal meaning	Public output or run effect
searchTerm	One keyword per line	The saved row keeps the matching value in searchTerm.
location	One Indian place per line	Each keyword is paired with each location. Empty means India-wide.
postedWithinDays	Source posting-age filter	It selects candidates. postedAt and postedAtRaw still come from the job.
sortBy	Source result order	It changes result order and rankOnPage. It does not change job facts.
experienceYears	Source experience filter	It selects candidates. The three experience fields still come from the job.
excludeCompanies	One company filter per line	Excluded jobs are not saved. OUTPUT.rowsExcludedByCompany counts them.
searchDepth	Coverage level for each keyword and location pair	searchDepthSearches and stopReason show when a search reaches the selected level.
maxItems	Optional saved-row limit after filters and duplicate removal	requestedMaxItems, rowsSaved, and stopReason show the effect. An omitted API value gives null.

Dataset rows and OUTPUT contain only the documented public fields.

Ordered public row contract

Every saved row uses these 30 fields in this order:

schemaVersion
jobId
title
companyName
location
experienceRaw
experienceMinYears
experienceMaxYears
salaryRaw
salaryMin
salaryMax
salaryCurrency
salaryPeriod
skills
descriptionText
postedAt
postedAtRaw
jobUrl
companyLogoUrl
companyRating
companyReviewCount
searchTerm
searchLocation
sourceUrl
pageNumber
rankOnPage
status
statusReason
source
observedAt

⚙️ Can I use this Actor through an API?

Yes. You can run Naukri Jobs Scraper in Apify Console or through:

• 🔌 Apify API
• 🐍 Python SDK
• 🟩 Node.js SDK
• 🪝 Webhooks
• ⏰ Scheduled runs
• 🧩 Apify integrations

This makes the Actor useful for job alerts, recruiting pipelines, job boards, dashboards, warehouse loads, and labor-market research.

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('chronometrica/naukri-jobs-scraper').call({
    searchTerm: 'data engineer',
    location: 'Bengaluru',
    maxItems: 100,
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

The input form starts with maxItems: 500. To remove the saved-row limit in an API run, omit maxItems from the JSON input. Search coverage, source inventory, run timeout, and the Apify charge limit can still stop the run.

🎯 Why scrape Naukri jobs?

Naukri is a main source of job listings in India. Its public listings can help you measure hiring demand and find active roles across Indian markets.

Use case	How the data helps
📈 Track hiring demand	Compare job volume by role, skill, city, or company.
🔔 Build job alerts	Schedule recent searches and route new rows to another tool.
💰 Study salary signals	Compare the salary ranges that employers publish.
🪜 Study experience demand	Measure requested experience by role and location.
🏢 Watch company hiring	Track public hiring activity by company search terms.
🧱 Build job data products	Load stable job IDs and clean rows into apps and databases.

💵 Pricing event

Naukri Jobs Scraper uses Pay per Event pricing. The price is $0.00125 per saved job, or $1.25 per 1,000 saved jobs. Platform usage is included.

One result charge occurs when the Actor saves one row to the default dataset. Failed requests, duplicate candidates, filtered candidates, and zero-row searches do not cause result charges.

Saved rows	Actor charge
100	$0.125
1,000	$1.25
10,000	$12.50

Use maxItems to set one shared saved-row limit. The input form starts at 500. An API run has no saved-row limit when its JSON input omits maxItems. Start with 10 to 100 rows when you test a new search. Check the Pricing tab for the active rate before a large run.

If the Apify result charge limit is near, the Actor stops before it writes a row that cannot be charged. OUTPUT.stopReason then becomes budget_cap_reached.

🚀 How do I use Naukri Jobs Scraper?

1. Create or log in to your Apify account.
2. Open Naukri Jobs Scraper.
3. Enter one or more job titles, skills, or company names.
4. Add Indian cities or regions, or leave locations empty for India-wide results.
5. Keep the 500-row limit or set another positive number.
6. Keep the default settings for your first run.
7. Click Start.
8. Open the Output tab to inspect the dataset and run summary.
9. Download the rows as JSON, JSONL, CSV, Excel, XML, RSS, or HTML.

⬇️ Input

This small example searches two role terms in Bengaluru. It uses one shared 25-row limit after filters and duplicate removal.

{
    "searchTerm": "data engineer\nanalytics engineer",
    "location": "Bengaluru",
    "postedWithinDays": "7",
    "maxItems": 25
}

🔎 Search matrix

Enter one keyword or location per line. The Actor creates one search pair for each keyword and location combination. Two keywords and three locations create six search pairs. A run can contain up to 200 pairs. If location is empty, each keyword creates one India-wide pair.

The Actor shares coverage across active search pairs. When set, maxItems is one shared saved-row limit for the whole run.

🎛️ Settings

Input	Allowed value	Default or blank behavior	Row, time, or cost effect
searchTerm	1 to 50 non-empty lines	Required	More terms can increase search coverage and run time.
location	0 to 20 Indian places, one per line	Empty means India-wide	More locations increase the search-pair count and run time.
maxItems	Positive integer	Form: 500; API omission: no saved-row limit	Sets an optional shared saved-row limit. It is a maximum, not a promise.
postedWithinDays	0, 1, 3, 7, 15, or 30	7; 0 means any time	A shorter window can return fewer jobs.
experienceYears	Integer from 0 to 30	Not set	Narrows source results. 0 includes fresher jobs.
sortBy	relevance or date	relevance	Changes result order, not row fields.
excludeCompanies	Company names, one per line	Empty	Matching jobs are filtered and not charged.
searchDepth	standard, extended, or deep	standard	A higher level can increase coverage and run time.

The JSON API also accepts the earlier searchTerms and locations arrays. Set failOnNoResults to true in JSON API input when an empty dataset must fail the run.

The Actor always saves one row per jobId in each run. This rule keeps the row grain stable and prevents duplicate result charges.

⬆️ Output sample

This sample shows all public fields in contract order. Live values depend on the job and observation time.

{
    "schemaVersion": "2026-08-15",
    "jobId": "150826123456",
    "title": "Senior Data Engineer",
    "companyName": "Example India",
    "location": "Bengaluru",
    "experienceRaw": "3-7 Yrs",
    "experienceMinYears": 3,
    "experienceMaxYears": 7,
    "salaryRaw": "12-18 Lacs PA",
    "salaryMin": 1200000,
    "salaryMax": 1800000,
    "salaryCurrency": "INR",
    "salaryPeriod": "year",
    "skills": ["Python", "SQL", "Airflow"],
    "descriptionText": "Build trusted data systems.",
    "postedAt": "2026-08-13T12:00:00.000Z",
    "postedAtRaw": "2 Days Ago",
    "jobUrl": "https://www.naukri.com/job-listings-senior-data-engineer-150826123456",
    "companyLogoUrl": null,
    "companyRating": 4.2,
    "companyReviewCount": 321,
    "searchTerm": "data engineer",
    "searchLocation": "Bengaluru",
    "sourceUrl": "https://www.naukri.com/data-engineer-jobs-in-bengaluru?k=data%20engineer&l=Bengaluru",
    "pageNumber": 1,
    "rankOnPage": 1,
    "status": "ok",
    "statusReason": null,
    "source": "naukri.com",
    "observedAt": "2026-08-15T12:00:00.000Z"
}

📌 Run summary

The OUTPUT record has one run-level state. It is not a dataset row and does not cause a result charge. It includes:

• Actor name, schema version, status, and run times.
• Requested saved-row limit, or null when omitted.
• Searches queued and finished.
• Pages requested and candidates seen.
• Rows saved, duplicate candidates skipped, and companies filtered.
• Blocked and failed request counts.
• Source-state counts and unique warning messages.
• Per-search page, candidate, row, duplicate, filter, and end-reason counts.
• Final stopReason.

Possible stop reasons are:

• max_items_reached
• source_exhausted
• search_depth_reached
• filtered_out
• blocked
• failed
• budget_cap_reached

🎯 Status, quality, and time fields

Saved job rows use status: "ok". Candidate failures, duplicate candidates, filtered candidates, and empty searches stay out of the paid dataset. The OUTPUT run state counts these outcomes.

• salaryRaw keeps the source salary text. Numeric salary fields are null when the text does not support a clear value.
• experienceRaw keeps the source experience text. Numeric experience fields are null when the text cannot be parsed safely.
• postedAtRaw keeps the source posting label. postedAt is a normalized time when the source value can support it.
• observedAt is the time when the run started observing its job rows.
• pageNumber and rankOnPage describe the search appearance that supplied the saved row.

✅ Release evidence

The private release gate on 2026-08-15 recorded:

• 250 saved rows with 250 descriptions and 250 result charges.
• 69 duplicate candidates skipped in that scale run.
• Zero blocked requests and zero failed requests in the final gates.
• Two 100-row repeat panels with the same 100 job IDs.
• Stable title, company name, and canonical job URL for all 100 repeated jobs.
• A duplicate test with 40 skipped duplicates.
• A filtered test with 20 excluded jobs and zero result charges.
• An empty-source test with zero rows and zero result charges.

This is dated release evidence. Live Naukri inventory and source behavior can change after this test.

🔒 Source boundary

The Actor collects logged-out public job listing data from the main Naukri India site. It does not collect:

• NaukriGulf jobs.
• Candidate profiles or private account data.
• Job applications or account actions.
• Login sessions, user cookies, or user credentials.
• Data hidden behind a CAPTCHA or another access control.

⚠️ Limits and interpretation

• When set, maxItems is a maximum. Filters, duplicate removal, search coverage, source inventory, a block, or a charge limit can return fewer rows.
• When an API input omits maxItems, the Actor has no saved-row limit. Search coverage, source inventory, run timeout, and the Apify charge limit still apply.
• Naukri can hide salary, rating, description, or posting values. These values stay null when they are not public or cannot be parsed safely.
• Live result order and job inventory can change between runs.
• The Actor keeps the first observed search appearance for each jobId. It does not save every rank for the same job.
• A public request can be blocked or challenged. The run state reports the final source result without solving the challenge.
• The Actor returns fields that are available in public Naukri listings.

❓ FAQ

Is Naukri the main India site?

Yes. This Actor covers the main Naukri India site. It does not cover NaukriGulf.

Does this Actor need login, cookies, or an API key?

No. It uses logged-out public job listing data.

Why did I get fewer jobs than maxItems?

maxItems is a shared maximum after filters and duplicate removal. Check OUTPUT for candidate, duplicate, filter, page-limit, source-state, and stop reason counts.

How do I remove the saved-row limit?

Use the JSON API and omit maxItems from the input. OUTPUT.requestedMaxItems will be null. Other stop conditions still apply.

Why can salary or posting time be null?

Naukri does not publish every value for every job. The Actor keeps uncertain values as null instead of making a value.

How do I avoid duplicate jobs?

The Actor saves each jobId once per run.

Why can some job fields be missing?

Naukri does not publish every field for every listing. Missing public values stay null.

What happens when no jobs are saved?

The Actor writes OUTPUT with the stop reason. It completes with a zero-row dataset by default. Set failOnNoResults to true if your automation must fail on this state.

⚖️ Responsible use

Use the Actor only for lawful purposes. Follow applicable laws, Naukri terms, and data protection rules. Do not use the output for spam or unfair automated decisions.

Naukri is a trademark of its owner. This Actor is independent. Naukri does not endorse or sponsor it.

🛟 Support

For support, include the Actor run ID, the input, the expected result, and one sample row when possible. State whether the issue affects one row or the full run. Do not send cookies or credentials.

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