Naukri.com Job Scraper

Turn Naukri job search into a recruiter-ready spreadsheet in minutes.

Export fresh Naukri.com listings as a flat dataset with a variable-length skills array plus CSV-friendly columns—ready for Google Sheets, Airtable, your ATS, CRM, or BI stack. Built for recruiters, sales teams, and automation builders who need clean hiring data without writing a custom parser.

Run on Apify · Try example input

Actor name: naukri-job-scraper

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The problem — and the fix

Pain	This Actor
Nested JSON breaks Sheets and CRM imports	Flat schema with skills array + export columns
Sourcing lists fill up with stale jobs	freshnessDays plus parsed-date post-filtering
Hours spent cleaning salary and skills text	Parsed salaryMin, salaryMax, and skills array (plus skills/0–skills/7 for CSV)
Runs die on blocks with nothing saved	Sessions, retries, proxy support, and partial-result recovery

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Who it's for

Recruiters and staffing

• Build fresh sourcing lists with experience bands, walk-in flags, and company ratings.
• Filter by location, work type, and how recently jobs were posted.
• Spot walk-in drives and employer reputation before you reach out.

Typical workflow: Search by role and city → export to Sheets or your ATS → start outreach the same day.

Sales and GTM

• Find companies actively hiring for roles you sell into.
• Target accounts with company name, rating, review count, and job URL in every row.
• Track remote, hybrid, and office demand by market.

Typical workflow: Run weekly searches by keyword → push dataset to your CRM → trigger outreach when hiring signals match your ICP.

Builders and ops

• Pipe jobs into Apify datasets, webhooks, or scheduled runs—no scraper maintenance.
• Choose fast listing mode or full descriptions depending on volume and cost.
• Rely on deduplication, block detection, and incremental dataset push for production pipelines.

Typical workflow: apify call or Console schedule → download CSV/JSON → feed Sheets, Airtable, or your data warehouse.

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Why teams switch from basic scrapers

What you need	Basic Naukri scraper	This Actor
CRM or Sheets import	Manual JSON cleanup	Flat schema + skills JSON array
Fresher or band hiring	Single experience value	experienceMin + experienceMax range
Only recent openings	Sort-only or coarse filter	freshnessDays + parsed-date filtering
Salary benchmarking	Raw salary text only	Raw salary + salaryMin / salaryMax
Skills reporting	Nested arrays	skills array (any length) + first 8 in skills/0–skills/7
Walk-in campaigns	Often missing	isWalkin on every row
Cost vs depth	Fixed behavior	Fast listing mode or full-description mode
Clean account lists	Basic URL dedup	Job ID → URL → title/company/location fallback
Long or fragile runs	Basic retries	Sessions, block detection, proxy, recovery

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Built for production runs

• CSV-ready: flat job fields plus skills array; first 8 skills also in skills/0–skills/7.
• Incremental export: jobs land in the dataset as they are scraped.
• Smart dedup: job ID, then URL, then title/company/location fallback.
• Resilient sessions: rotate when blocks or rate limits appear; retry failed requests.
• Your pace: optional fast listing scrape or full job descriptions from detail pages.
• Proxy-ready: Apify Proxy enabled by default; tune delays when sites get strict.

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Quick start

First run in 60 seconds

1. Set keyword (e.g. software engineer).
2. Set location (e.g. Bangalore).
3. Set maxItems (e.g. 50).
4. Click Start on Apify Console—or run the CLI below.

Run on Apify

apify push
apify call naukri-job-scraper --input='{"keyword":"product manager","location":"Delhi","maxItems":50}'

Open Apify Console to configure inputs in the UI, view the Output table, and download CSV or JSON.

Run locally

npm install -g apify-cli && apify login
cd <your-repo-clone> && npm install && apify run

Dataset from the last run: apify dataset get default (files also under storage/datasets/default/).

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Example inputs

Fresher fullstack — tight sourcing list

Use when you need recent, junior fullstack roles with full descriptions for screening.

{
  "keyword": "fullstack developer",
  "location": "Bangalore",
  "experienceMin": 0,
  "experienceMax": 2,
  "freshnessDays": 5,
  "strictFreshness": true,
  "sortBy": "date",
  "maxItems": 100,
  "includeDescriptions": true
}

Fast listing — high volume, lower cost

Use when you want large exports quickly without opening every job detail page.

{
  "keyword": "data analyst",
  "location": "Mumbai",
  "maxItems": 200,
  "includeDescriptions": false,
  "sortBy": "relevance",
  "minDelaySeconds": 2,
  "maxDelaySeconds": 4,
  "blockResources": true
}

Remote product manager — GTM or market scan

Use when you track who is hiring remotely and only want jobs from the last week.

{
  "keyword": "product manager",
  "location": "India",
  "workType": "remote",
  "freshnessDays": 7,
  "sortBy": "date",
  "maxItems": 150,
  "includeDescriptions": false
}

---

Technical reference

Everything below is for configuration, integration, and troubleshooting.

Input fields

Field	Type	Required	Default	Description
keyword	string	Yes	-	Job search keyword, e.g. "software engineer"
location	string	No	""	Location filter, e.g. "Bangalore", "Mumbai", "India"
experience	integer	No	-	Legacy minimum experience; prefer experienceMin / experienceMax
experienceMin	integer	No	-	Minimum years of experience (0–50)
experienceMax	integer	No	-	Maximum years of experience (0–50)
sortBy	string	No	"relevance"	"relevance" or "date"
workType	string	No	""	"", "office", "remote", or "hybrid"
freshnessDays	integer	No	-	Keep jobs posted within the last N days (1–30)
strictFreshness	boolean	No	true	Exclude jobs with unknown posted dates when freshnessDays is set
maxItems	integer	No	50	Maximum jobs to scrape (1–1000)
includeDescriptions	boolean	No	true	Visit detail pages and extract full descriptions
proxyConfiguration	object	No	{ "useApifyProxy": true }	Apify proxy settings
minDelaySeconds	integer	No	2	Minimum random delay between requests (0–30)
maxDelaySeconds	integer	No	6	Maximum random delay between requests (0–60)
blockResources	boolean	No	true	Block images, fonts, and media for faster runs
debugSnapshots	boolean	No	false	Save HTML snapshots on errors for debugging

Output fields

One flat JSON object per job:

title
companyLogo
companyName
companyRating
companyReviewCount
description
experience
isWalkin
jobId
jobUrl
location
postedDate
salary
salaryMax
salaryMin
scrapedAt
skills
skills/0
skills/1
skills/2
skills/3
skills/4
skills/5
skills/6
skills/7

Output example

{
  "title": "Fullstack Developer",
  "companyLogo": "https://img.naukimg.com/companyimages/...",
  "companyName": "TechCorp",
  "companyRating": 4.2,
  "companyReviewCount": 801,
  "description": "We are looking for...",
  "experience": "0-2 Yrs",
  "isWalkin": false,
  "jobId": "12345678",
  "jobUrl": "https://www.naukri.com/job-listings-...",
  "location": "Bengaluru",
  "postedDate": "2024-01-10T08:00:00.000Z",
  "salary": "10-15 Lacs PA",
  "salaryMax": 15,
  "salaryMin": 10,
  "scrapedAt": "2024-01-15T10:30:00.000Z",
  "skills": ["Python", "React"],
  "skills/0": "Python",
  "skills/1": "React",
  "skills/2": null,
  "skills/3": null,
  "skills/4": null,
  "skills/5": null,
  "skills/6": null,
  "skills/7": null
}

Skills fields: skills holds every skill for the job (0 to many). skills/0–skills/7 duplicate the first eight for spreadsheet imports; jobs with more than eight skills only show extras in skills.

On Apify Console, the run Output tab shows this schema in a table; Storage holds INPUT, scraper state, and optional debug snapshots.

How filtering works

Experience: When both experienceMin and experienceMax are set, the Actor uses the matching Naukri experience slug and validates parsed experience text from listings.

Freshness: With freshnessDays, the Actor applies the nearest Naukri job-age filter on the search URL, then post-filters by parsed posted date. strictFreshness: true drops jobs with unknown dates; false keeps unknown-date jobs but still removes known stale ones.

Description mode:

Mode	Best for	Behavior
includeDescriptions: false	Fast exports, larger sets, lower cost	Data from listing cards only
includeDescriptions: true	ATS import, full-text search	Opens detail pages for full descriptions

Reliability notes

• Jobs are pushed to the dataset as soon as they are extracted.
• Duplicates are skipped via job ID, normalized URL, then title/company/location.
• Sessions retire on block or rate-limit signals; failed requests retry.
• Enable debugSnapshots when selectors need investigation.
• blockResources reduces page weight while keeping useful Naukri assets.

Limitations

• Public Naukri job listings only—no login, CAPTCHA bypass, or paywall access.
• Some fields may be empty when Naukri does not show them.
• Selectors may need updates if Naukri changes page structure.
• Very strict filters can return fewer jobs than maxItems.

Troubleshooting

Issue	Likely cause	What to try
No jobs found	Filters too narrow	Broaden keyword, location, experience, or freshness
Fewer jobs than expected	strictFreshness removing unknown dates	Set strictFreshness to false
Slow runs	Detail pages enabled	Set includeDescriptions to false
Missing descriptions	Detail page failed or changed	Enable debugSnapshots and inspect HTML
Missing salary min/max	Unparseable salary text	Use raw salary as fallback
HTTP 403 or blocks	Proxy or session flagged	Keep Apify Proxy on; increase delays
Duplicate-looking jobs	Naukri reposts similar listings	Match on jobId and title/company/location

Compliance

This Actor collects only publicly visible job listing information. It does not access private user data, bypass login walls, solve CAPTCHAs, or evade access controls.

You are responsible for use that complies with Naukri.com terms, applicable laws, privacy rules, and your organization’s policies. Use reasonable crawl rates and cache results where possible.