Naukri Job Scraper

Naukri Job Scraper creates a structured dataset of job listings collected from Naukri.com. Each dataset item represents one job listing and can include title, company, location, experience, salary, skills, work mode, posting dates, and rating. Optional job-detail, company-overview, and AmbitionBox review fields attach to the same row. Query the source with keywords plus locations, Naukri search or listing URLs, or company pages. Control the result limit with maxJobs, and retrieve records through the Apify Dataset API or export them as JSON, CSV, Excel, or another supported format.

Dataset at a glance

Property	Value
Source	naukri.com (job listings; optional AmbitionBox reviews)
Record unit	One job listing, with optional nested company and review fields
Input methods	Keyword + location search (searchQueries, locations), Naukri URLs (startUrls), or company pages (companyUrls)
Main identifiers	jobId, url
Delivery	Apify Dataset and API
Export formats	JSON, CSV, Excel, XML, HTML (Apify dataset exports)
Update model	Fresh records per Actor run
Pricing	$3.00 per 1,000 jobs; +$3.00 per 1,000 job details; +$3.00 per unique company overview; +$2.00 per 1,000 reviews

Coverage and available records

The Actor collects public Naukri job listings from three entry points. They can be combined in one run.

• Search-based: Set searchQueries to job titles, skills, or keywords (for example python developer). Each query is searched in every value in locations. Leave locations empty for a nationwide search. sortBy, freshness, and workMode apply to these keyword searches.
• URL-based: Pass Naukri search pages or job listing URLs in startUrls. Those URLs are used in addition to keyword searches.
• Company-based: Pass Naukri company overview pages (for example https://www.naukri.com/infosys-overview-13832) or AmbitionBox review pages (for example https://www.ambitionbox.com/reviews/infosys-reviews) in companyUrls. Live jobs for that company are collected up to maxJobs.

Record types and limits:

• Listing records are always collected: jobId, title, company, URL, location, experience, salary, skills, work mode, posting fields, rating, and the source query when the row came from search.
• Job-detail fields are conditional: full description, expanded skills, education, and apply/view counts are returned only when scrapeJobDetails is enabled.
• Company overview fields are conditional: size, headquarters, followers, type, founded year, about text, and offices attach onto each job from that company when scrapeCompanyOverview is enabled. The overview is collected once per unique company.
• Review records are conditional: an AmbitionBox reviews array attaches onto each job from that company when scrapeCompanyReviews is enabled, up to maxReviewsPerCompany (default 20; 0 means unlimited).
• Result cap: maxJobs limits the number of job rows (0 means unlimited, the default). Company overview fields and reviews are attached onto those rows; they are not extra dataset items.

Known exclusions: content Naukri or AmbitionBox only shows behind login is not collected; each run captures page state at run time (no historical snapshots); freshness and workMode filters apply to keyword/location searches, not to arbitrary start URLs.

Data dictionary

Field names below match dataset record JSON properties exactly. Fields marked conditional appear only when the corresponding input toggle is enabled. jobId is the recommended deduplication key; url is a reasonable secondary key.

Listing fields

Field	Type	Nullable	Description	Example
jobId	string	No	Naukri job identifier; best stable deduplication key	150126031660
title	string	No	Job title as listed	Python Developer (@Infosys)
companyName	string	No	Hiring company name	Infosys
url	string	No	Job listing URL	https://www.naukri.com/job-listings-python-developer-infosys-infosys-kolkata-hyderabad-bengaluru-5-to-10-years-150126031660
companyUrl	string	Yes	Naukri company overview URL	https://www.naukri.com/infosys-overview-13832
location	string	Yes	Job location as listed (may include multiple cities)	Kolkata, Hyderabad, Bengaluru
experience	string	Yes	Experience range as shown on Naukri	5-10 Yrs
minimumExperience	integer	Yes	Minimum years of experience	5
maximumExperience	integer	Yes	Maximum years of experience	10
salary	string	Yes	Salary as shown on the listing	Not disclosed
postedAgo	string	Yes	Relative posting age as rendered on Naukri	7 Days Ago
postedDate	string	Yes	Posting timestamp (ISO 8601)	2026-08-11T10:39:09.094000+00:00
skills	string[]	Yes	Skills shown on the listing	["Django", "Python", "Flask"]
workMode	string	Yes	Work arrangement when shown (Hybrid, Remote, or office)	Hybrid
diversityTag	string	Yes	Diversity label when Naukri shows one	Prefers women
rating	number	Yes	Company rating (typically AmbitionBox, 0–5)	3.5
reviewCount	integer	Yes	Company review count shown on the listing	50508
sourceQuery	string	Yes	Search keyword that produced the row	python developer
sourceLocation	string	Yes	Location used in the search	bangalore
itemType	string	No	Record type; always job on dataset rows	job

Job-detail fields (conditional — scrapeJobDetails)

Field	Type	Nullable	Description	Example
description	string	Yes	Full job description	Long-form text
skills	string[]	Yes	Listing skills expanded with detail-page skills	["Django", "Python", "Flask"]
education	object	Yes	{undergraduate, postgraduate, doctorate} string arrays	See nested object
applyCount	integer	Yes	Number of applications shown on the listing	Null when the listing does not show a count
viewCount	integer	Yes	Number of views shown on the listing	Null when the listing does not show a count
employmentType	string	Yes	Employment type when the detail page provides it	permanent

Company overview fields (conditional — scrapeCompanyOverview)

These fields attach onto every job row from that company. The overview is fetched once per unique company.

Field	Type	Nullable	Description	Example
companySize	string	Yes	Employee-size bucket	100001+
headquarters	string	Yes	Headquarters as shown on the company page	Bengaluru
followCount	integer	Yes	Naukri follower count	1878902
companyType	string	Yes	Organisation type	Public
founded	string	Yes	Founding year as shown on the company page	1981
companyAbout	string	Yes	Company about text	Infosys is a global leader in next-generation digital services and consulting.
companyOffices	object[]	Yes	Offices: {city, address, pincode, isHeadquarter}	See example record

Review fields (conditional — scrapeCompanyReviews)

Each job record may include a reviews array from AmbitionBox. One review object:

Field	Type	Nullable	Description	Example
reviewId	integer	No	AmbitionBox review identifier	78544194
title	string	Yes	Review title	rated by a Technical Lead in Bengaluru
rating	number	Yes	Overall company rating on the review (0–5)	1.0
likes	string	Yes	What the reviewer liked	Culture and env.
dislikes	string	Yes	What the reviewer disliked	Manager are no supportive...
department	string	Yes	Reviewer department	Software Development
location	string	Yes	Reviewer location	Bengaluru
jobProfile	string	Yes	Reviewer job title	Technical Lead
employmentType	string	Yes	Employment type on the review	permanent
workPolicy	string	Yes	Work policy on the review	Hybrid
postedAgo	string	Yes	Relative review date as rendered	14 Aug 2026
verified	boolean	Yes	Whether AmbitionBox marks the review verified	false

Example dataset record

Representative record from a python developer search in bangalore, with company overview and reviews enabled. companyAbout is shortened for length; the JSON below is valid. The reviews array is limited to one item for readability.

{
  "jobId": "150126031660",
  "title": "Python Developer (@Infosys)",
  "companyName": "Infosys",
  "url": "https://www.naukri.com/job-listings-python-developer-infosys-infosys-kolkata-hyderabad-bengaluru-5-to-10-years-150126031660",
  "companyUrl": "https://www.naukri.com/infosys-overview-13832",
  "location": "Kolkata, Hyderabad, Bengaluru",
  "experience": "5-10 Yrs",
  "minimumExperience": 5,
  "maximumExperience": 10,
  "salary": "Not disclosed",
  "postedAgo": "7 Days Ago",
  "postedDate": "2026-08-11T10:39:09.094000+00:00",
  "skills": ["Django", "Python", "Flask", "Angularjs", "Full Stack", "Angular"],
  "workMode": "Hybrid",
  "diversityTag": "Prefers women",
  "rating": 3.5,
  "reviewCount": 50508,
  "sourceQuery": "python developer",
  "sourceLocation": "bangalore",
  "companySize": "100001+",
  "headquarters": "Bengaluru",
  "followCount": 1878902,
  "companyType": "Public",
  "founded": "1981",
  "companyAbout": "Infosys is a global leader in next-generation digital services and consulting.",
  "companyOffices": [
    {
      "city": "Bengaluru",
      "address": "Infosys, Plot No.44 Hosur Main Road, Electronics City",
      "pincode": "Karnataka 560100",
      "isHeadquarter": true
    }
  ],
  "reviews": [
    {
      "reviewId": 78544194,
      "title": "rated by a Technical Lead in Bengaluru",
      "rating": 1.0,
      "likes": "Culture and env.",
      "dislikes": "Manager are no supportive...",
      "department": "Software Development",
      "location": "Bengaluru",
      "jobProfile": "Technical Lead",
      "employmentType": "permanent",
      "workPolicy": "Hybrid",
      "postedAgo": "14 Aug 2026",
      "verified": false
    }
  ],
  "itemType": "job"
}

A matching input for that record shape:

{
  "searchQueries": ["python developer"],
  "locations": ["bangalore"],
  "maxJobs": 20,
  "scrapeCompanyOverview": true,
  "scrapeCompanyReviews": true,
  "maxReviewsPerCompany": 20,
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": ["RESIDENTIAL"]
  }
}

Job-detail fields such as description, education, applyCount, and viewCount appear when scrapeJobDetails is enabled.

Query and input reference

Input	Type	Required	Default	Accepted values	Description
searchQueries	string[]	No*	[]	Job titles, skills, or keywords	Combined with each location. Prefill: python developer
locations	string[]	No	[]	Indian cities or regions as shown on Naukri	Each query is searched in every location. Empty = nationwide. Prefill: bangalore
startUrls	array (requestListSources)	No*	[]	Naukri search pages or /job-listings-... URLs	Used in addition to search queries
companyUrls	array (requestListSources)	No*	[]	Naukri overview or AmbitionBox review pages	Collects live jobs for that company up to maxJobs
maxJobs	integer	No	0	0 or any positive integer	Maximum job rows; 0 = unlimited. Overview and reviews attach onto those rows
sortBy	string	No	relevance	relevance, date	Search-result sort (date is newest first)
freshness	string	No	any	any, 1, 3, 7, 15, 30	Posted-within window for keyword/location searches (days)
workMode	string	No	any	any, office, hybrid, remote	Work-arrangement filter for keyword/location searches
scrapeJobDetails	boolean	No	false	true / false	Collect full description, skills, education, and apply/view counts (charged as job-details)
scrapeCompanyOverview	boolean	No	false	true / false	Attach company profile fields onto each job (charged once per unique company)
scrapeCompanyReviews	boolean	No	false	true / false	Attach AmbitionBox reviews onto each job (charged per review)
maxReviewsPerCompany	integer	No	20	0 or any positive integer	Review cap per company; 0 = unlimited. Ignored when reviews are disabled
detailConcurrency	integer	No	5	1–20	Maximum parallel job-detail and company requests
proxyConfiguration	object	No	Apify proxy, RESIDENTIAL group	Apify proxy groups or custom proxies	Residential proxies are recommended

* Provide at least one of searchQueries, startUrls, or companyUrls.

Minimal request:

{ "searchQueries": ["python developer"], "locations": ["bangalore"], "maxJobs": 20 }

Advanced request (search filters plus a company page and enrichment):

{
  "searchQueries": ["python developer"],
  "locations": ["bangalore"],
  "companyUrls": [{ "url": "https://www.naukri.com/infosys-overview-13832" }],
  "maxJobs": 100,
  "sortBy": "date",
  "freshness": "7",
  "workMode": "hybrid",
  "scrapeJobDetails": true,
  "scrapeCompanyOverview": true,
  "scrapeCompanyReviews": true,
  "maxReviewsPerCompany": 20,
  "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": ["RESIDENTIAL"] }
}

Retrieve the data through the API

The Actor runs on the Apify platform, so there is no server to host and no crawling infrastructure to maintain.

1. Start the Actor with a JSON input (console or API).
2. Wait for the run to finish, or use a synchronous endpoint if you want the response inline.
3. Retrieve items from the run's default dataset.
4. Paginate or export the dataset.

Python example:

from apify_client import ApifyClient

client = ApifyClient("YOUR-APIFY-TOKEN")

run_input = {
    "searchQueries": ["python developer"],
    "locations": ["bangalore"],
    "maxJobs": 20,
    "scrapeJobDetails": True,
}

run = client.actor("datascrapers/naukri-scraper").call(run_input=run_input)
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item["jobId"], item["title"], item["companyName"])

Apify generates ready-to-run Python, JavaScript, and cURL examples on the Actor's API tab. Do not put a real API token in shared code or URLs.

Data quality and record handling

• Conditional fields: job-detail, company-overview, and review fields are present only when their input toggle is enabled. Listing-only runs return a leaner record.
• Attached enrichments: company overview and reviews are nested on the job row. A company with 20 reviews still produces one dataset item per job, not extra rows.
• Source changes: Naukri and AmbitionBox page structure and values can change; unreadable fields are returned as null rather than fabricated. Salary is often the string Not disclosed.
• Deduplication: within a run, listings are deduplicated by jobId. Across runs, use jobId (or url) as the stable key and filter against previously stored IDs.
• Detail fallback: listing data is returned even when job-detail enrichment fails.
• Normalization: minimumExperience and maximumExperience are integers; postedDate is ISO 8601; skills is a string array. sourceQuery and sourceLocation are written on search-produced rows.
• Location spelling: keyword search locations should match Naukri's search labels (for example bangalore). Listing text may use a different spelling (for example Bengaluru).

Export and pipeline examples

Destination	Recommended method	Typical use
PostgreSQL / Supabase	Dataset API poll or webhook consumer	Store job listings alongside talent tables
Google Sheets	Apify Google Sheets integration	Share role shortlists with recruiting teams
CRM / ATS pipeline	Webhook on run completion	Push new listings into applicant tracking
S3 / cloud storage	Scheduled export via Apify scheduler + integration	Archival of labor-market snapshots

Pricing and cost examples

The Actor uses pay-per-event pricing. Events are tiered by Apify plan. Published event rates:

Event	Trigger	Rate
Actor start	Once per run	$0.00005
dataset-item	Every job record pushed to the dataset	$0.003 / job ($3.00 per 1,000 jobs)
job-details	scrapeJobDetails enabled, detail data fetched	$0.003 / job ($3.00 per 1,000 jobs)
company-overview	scrapeCompanyOverview enabled, once per unique company	$0.003 / company ($3.00 per 1,000 companies)
company-reviews	scrapeCompanyReviews enabled, per AmbitionBox review	$0.002 / review ($2.00 per 1,000 reviews)

Example costs at the published event rates (Actor start is $0.00005 per run):

Records	Configuration	Estimated base cost
1,000 jobs	Listing only	$3.00
10,000 jobs	Listing only	$30.00
1,000 jobs	Listing + job details	$6.00
1,000 jobs + 200 unique companies	Listing + company overview	$3.60
1,000 jobs + 1,000 reviews	Listing + reviews	$5.00
1,000 jobs + details + 200 overviews + 1,000 reviews	All enrichments	$8.60

Paid Apify plans apply lower tiered event rates. Compute units consumed by the run are billed by your Apify plan. Estimates depend on the verified pricing model, unique-company count, review volume, and the options selected for the run.

Limitations and responsible data use

• The Actor collects publicly accessible data from Naukri job and company pages, and from AmbitionBox review pages when reviews are enabled.
• Field availability depends on what the source renders at run time; some values can be null or missing, and site changes can alter fields.
• freshness and workMode apply to keyword/location searches. Location values should match Naukri search labels.
• Company overview and reviews attach onto job rows; they are not standalone dataset items.
• The Actor does not provide historical snapshots unless you store them yourself.
• You are responsible for compliance with Naukri and AmbitionBox terms of service, applicable privacy law, and any contractual obligations before using the data.

Dataset questions

What does one dataset item represent?

One Naukri job listing. Company overview fields and AmbitionBox reviews attach onto that job row. A job whose company has 20 reviews still produces a single dataset item.

Which field should I use as a unique identifier?

jobId is the stable Naukri job identifier and is the recommended deduplication key. The url is a reasonable secondary key.

Are fields nullable or conditional?

Yes. Job-detail fields exist only when scrapeJobDetails is enabled; company overview fields exist only when scrapeCompanyOverview is enabled; the reviews array exists only when scrapeCompanyReviews is enabled. Within available records, fields the listing does not render are returned as null. salary is often the string Not disclosed.

How do I collect live jobs for one company?

Add the Naukri overview URL or AmbitionBox review URL to companyUrls. The Actor collects that company's live jobs up to maxJobs and attaches overview and review fields onto those rows when the corresponding toggles are on.

Can I retrieve the records as CSV or JSON?

Yes. The dataset can be exported as JSON, CSV, Excel, XML, or HTML from the Apify Console, and queried through the Dataset API.

Does the Actor return historical data?

No. Each run captures the state of the listings at run time. To track posting or salary changes, schedule repeated runs and store the outputs yourself.

What counts as a billable result?

Four pay-per-event charges apply after a $0.00005 Actor-start charge: a dataset-item charge for every job row ($3.00 per 1,000), a job-details charge for each enriched job ($3.00 per 1,000), a company-overview charge once per unique company ($3.00 per 1,000), and a company-reviews charge per AmbitionBox review ($2.00 per 1,000). A listing-only run incurs Actor start plus dataset-item charges.

Related datasets from Data Scrapers

• Glassdoor Jobs Scraper — Job listings with employer ratings that can be compared with Naukri rows by title, company, and location.
• ZipRecruiter Scraper — US job listings for cross-board labor-market comparison against Naukri India results.
• StepStone Jobs Scraper — European job listings useful for multi-region hiring-volume analysis.
• LinkedIn Company Scraper — Company profiles that can be joined with Naukri jobs by company name.
• LinkedIn Profile Scraper — Public professional profiles for talent and hiring research alongside Naukri openings.

Data Scrapers support

Need an additional field, record type, or export workflow? Contact Data Scrapers at stardustspotlight@gmail.com. Include a sample source URL, required fields, expected record volume, and preferred delivery format.