Naukri Scraper

Scrape Naukri public job listings and job identifiers from public pages and export Naukri data to CSV, JSON, or Excel. This Naukri API alternative turns repeatable inputs into structured jobs for India job-market tracking and vacancy discovery.

Each dataset row represents a public job or a documented alternate record type. The output includes source identifiers and links where available, so you can verify a row, compare later runs, and distinguish missing source data from an omitted column.

What data can you extract from Naukri?

The dataset schema defines every field below. Examples come from one successful published run; null means that field was not exposed for that particular record. Availability may differ by input mode, page, and record type.

Field	Description	Example
jobId	Source job identifier.	230926010009
jdURL	Direct job listing URL.	https://www.naukri.com/job-listings-staff-software-developer-node-js-react-aw…
title	Job title when available from the job endpoint.	null
companyName	Employer name when available.	null
location	Job location when available.	null
experience	Required experience when available.	null
salary	Published salary when available.	null
currency	Salary currency when available.	null
createdDate	Listing creation date when available.	null
jobDescription	Full description when detailed data is available.	null
tagsAndSkills	Published tags and skills when available.	null
companyJobsUrl	Employer jobs page when available.	null
companyId	Source employer identifier when available.	null
logoPath	Employer logo URL when available.	null
logoPathV3	Alternate employer logo URL when available.	null
ambitionBoxData	Public employer rating data when available.	null
footerPlaceholderLabel	Additional listing label when available.	null
footerPlaceholderColor	Display color of the additional label when available.	null
isSaved	Saved status when supplied by the endpoint.	null
showMultipleApply	Multiple-apply display flag when available.	null
groupId	Source group identifier when available.	null
isTopGroup	Top-group flag when available.	null
exclusive	Exclusive-listing flag when available.	null
brandingTags	Listing branding labels when available.	null
mode	Source listing mode when available.	null
board	Source job board when available.	null
source	Origin of the record: jobApi, sitemap, or inputUrl.	sitemap
sitemapLastModified	Last modification timestamp from the sitemap; this is not a posting date.	2026-09-26T02:24:23.900+05:30

Use the identifier and URL fields as your join keys before comparing snapshots. Fields that describe a page, search, category, author, or tournament establish where the record came from; keep them when you export a subset. Numeric values and boolean flags reflect the public page at collection time, not a permanent claim about the underlying item.

How to scrape Naukri

1. Open the actor input form and choose a narrow public source: a search phrase, page URL, item URL, or ID supported by the input fields below.
2. Set the relevant per-source page or result limit and the total item limit. Start with a small sample to check which optional fields the public source exposes.
3. Run the actor. Its dataset contains one structured row per saved result; inspect the first rows and their source links for the chosen input.
4. Download the dataset as JSON, CSV, or Excel. Preserve identifiers when combining runs so repeated results can be deduplicated.

For this actor, a keyword or search URL discovers jobs when the search endpoint is open. Job IDs or URLs take precedence. When a captcha blocks the endpoint, the sitemap can still return recent job IDs and URLs but not the missing job attributes.

Input

Use only the parameters relevant to your collection mode. An omitted optional filter uses the schema default shown here; an empty array, zero, and an omitted value can have different meanings, so keep intentional settings in your saved input.

| Parameter | Type | Default | Description | | --- | --- | --- | | keyword | string | No default; example software developer | Words to find in job listings. A search URL or job IDs take precedence. | | location | string | None | Optional city or region to narrow the search. | | searchUrl | string | None | A naukri.com search results URL. Its keyword and location take precedence over the separate fields. | | jobIds | array | None | Optional 12-digit job IDs or full job URLs to look up directly. Takes precedence over search. | | maxJobs | integer | 100 | Maximum number of unique jobs to save. | | fetchDetails | boolean | false | Request full job details when the source endpoint is available. Captcha-protected results remain partial. | | sortBy | string | relevance | Sort search results by relevance or date when the search endpoint is available. | | experience | string | all | Years of required experience for the search endpoint. Use all for no filter. | | freshness | string | all | Maximum posting age in days for the search endpoint. Use all for no filter. | | workMode | array | [] | Optional work modes for the search endpoint. | | proxyConfiguration | object | {"useApifyProxy":true} | Proxy configuration for fetching source pages. |

Example input based on the published golden run (long URL lists are shortened):

{
  "keyword": "software developer",
  "maxJobs": 40,
  "fetchDetails": false
}

The example is a starting shape, not a guarantee of a particular result count. Source inventory and page accessibility change. When you need repeatable comparisons, save the exact input JSON with the run date and inspect the returned source or record-type field.

Output example

The following is one real item from a successful published dataset. Long text and media arrays are shortened for readability; the actual dataset keeps the original values and all schema fields.

{
  "jobId": "230926010009",
  "jdURL": "https://www.naukri.com/job-listings-staff-software-developer-node-js-react-aws-ai-diligent-bengaluru-8-to-13-years-230926010009",
  "source": "sitemap",
  "sitemapLastModified": "2026-09-26T02:24:23.900+05:30"
}

This row illustrates the observed output structure, including its identifiers and public links. Empty values elsewhere in the dataset should be interpreted field by field; a field shown in this example is not promised for every job.

Use cases

• Recruiting analysts can track newly listed public job URLs and IDs by keyword.
• Labor-market researchers can measure the volume of recent vacancies when source coverage is available.
• Job boards can reconcile known Naukri URLs against their catalog without treating sitemap-only rows as complete vacancies.
• Hiring teams can gather available skills, salary, and employer fields when the detailed endpoint is open.

The strongest analyses keep source context. A field such as price, rating, engagement, or rank has meaning only with its associated item, query, date, and public URL. Keep the raw export and create a separate cleaned view for charts or alerts.

How much does it cost to scrape Naukri?

The price is $1.00 per 1,000 saved results. Platform usage is included. The charge scales with output rows, so a restrictive filter or inaccessible page can produce fewer billable results than the requested maximum.

• 100 jobs: $0.10. This is useful for checking a small cohort and confirming which optional fields are present.
• 1,000 jobs: $1.00. This is the reference price for a larger export.
• 5,000 jobs: $5.00. Reaching this size may require multiple focused sources or scheduled runs, depending on public inventory and source caps.

Compute any other estimate as saved result count × $1.00 / 1,000. A maximum input is a ceiling, not a purchase of that many rows. For planning, use the actual saved-item count from an initial representative run.

Tips for best results

Start with a narrow keyword and location. For a known role, provide jobIds directly. Enable fetchDetails only when title, employer, and full descriptions are needed; check source on each row before relying on optional attributes.

Collect a small baseline first, record the exact input and date, and inspect both a typical row and a sparse row. Expand by adding focused sources instead of assuming one broad input can reveal the full public inventory. When comparing two runs, match stable IDs or canonical URLs and use the same filters so changes reflect the source rather than a changed query.

Export the full JSON when nested arrays or objects matter. CSV and Excel are convenient for sorting and joins, but nested structures may need flattening before spreadsheet analysis. Keep numeric fields numeric and preserve source URLs as text; do not infer a zero from a null.

Limits

The successful golden run used the sitemap fallback: it returned identifiers and URLs, while title, company, location, and other job attributes were null. Search filters and detail enrichment may be ineffective during captcha periods.

Public pages can change, disappear, or expose different fields for different records. The schema is a list of possible output columns, not a promise that each column is filled in each row. The maxItems-style input limits cap saved results; they do not bypass source pagination, public visibility, or a site-specific result ceiling.

Treat a saved result as a snapshot. If a later run returns fewer rows, first compare the input, source access, and public inventory before concluding that the underlying market changed. If you need an audit trail, retain the source URL, stable identifier, and run timestamp with the export.

Use with AI agents (MCP)

An agent can supply the documented input JSON, run this actor, and work from its dataset. Ask it to keep source links and identify null values explicitly when summarizing results. Example prompts:

Run Naukri Scraper for the sample input above. Return the first 20 jobs with their source URLs and the fields needed for India job-market tracking and vacancy discovery. Mark unavailable fields as null.

Schedule a repeat Naukri collection with the same filters. Compare records by stable ID or canonical URL and report only new, removed, or changed public values.

FAQ

Is it legal to scrape Naukri?

This actor collects public data. Check the site’s terms, applicable law, and the rights of people whose data appears in your export. Follow GDPR and other privacy rules where relevant; do not use personal data for misuse, intrusive profiling, or unauthorized contact.

Do I need to configure proxies?

The input includes proxyConfiguration and defaults to Apify Proxy. Usually the default is enough to start. Availability can vary by page and region; changing network settings cannot make private or login-only information public.

How fast will a run finish?

Duration depends on the number of inputs, pages, detail requests, and source responses. A small sample is the best way to measure your workload. Increase the limits gradually, then use the observed run duration for scheduling and monitoring.

Can I schedule and monitor recurring runs?

Yes. Save the input and schedule recurring runs in Apify. Monitor run status, item count, and any missing-field changes; store the run date alongside exports when comparing snapshots.

Can I export to Google Sheets or Excel?

Yes. Download CSV or Excel from the dataset, or pass JSON to a spreadsheet integration. For nested fields, flatten the specific child values you need rather than losing the original JSON.

What if a field is empty?

An empty or null field means it was not available from that public source record in that run. Check the source URL, input mode, and record type. Do not replace missing prices, counts, dates, or flags with zero unless your own analysis has a documented rule for doing so.

Why are job titles and companies sometimes empty?

A captcha may block the search and job endpoints. The actor then uses the public incremental sitemap, which provides recent job IDs and URLs but not detailed job fields.

Integrations

Use the Apify API to start runs and retrieve the dataset, webhooks to react when a run finishes, or Zapier, Make, and n8n to route records into other systems. Google Sheets supports lightweight review, while scheduled runs provide repeat snapshots. Keep the raw JSON when downstream workflows need nested fields or exact null values.

Support

Open an issue on the Issues tab; we reply within 24h and add fields on request.