Naukri Job Scraper — India’s #1 Job Board avatar

Naukri Job Scraper — India’s #1 Job Board

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from $2.00 / 1,000 results

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Naukri Job Scraper — India’s #1 Job Board

Naukri Job Scraper — India’s #1 Job Board

Track Naukri.com jobs daily from $1.28/mo — incremental mode emits NEW, UPDATED, REAPPEARED, UNCHANGED, and EXPIRED listings with firstSeen/lastSeen timestamps (83–93% cheaper than full re-scrapes). Triple-format descriptions (HTML/plain/Markdown) for RAG and AI agents.

Pricing

from $2.00 / 1,000 results

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Black Falcon Data

Black Falcon Data

Maintained by Community

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26 minutes ago

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What does Naukri.com Job Scraper do?

Naukri.com Job Scraper extracts structured job data from naukrigulf.com — including salary data, contact details, company metadata, full descriptions, and skill tags. It supports keyword search, location filters, and controllable result limits, so you can run the same query consistently over time. The actor also offers detail enrichment (full descriptions and company metadata) where the source provides them.

Key features

  • Incremental mode — recurring runs emit and charge only for listings that are new or whose tracked content changed. First run builds the baseline state; subsequent runs emit only new or changed records.
  • Detail enrichment — full descriptions and company metadata where the source provides them.
  • Compact mode — AI-agent and MCP-friendly payloads with core fields only.

What data can you extract from naukrigulf.com?

Each result includes Core listing fields (jobId, title, experienceText, minimumExperience, maximumExperience, salary, salaryMin, and salaryMax, and more), detail fields when enrichment is enabled (description, descriptionHtml, descriptionMarkdown, roleCategory, and jobRole), contact and apply information (applyCount), and company metadata (companyName, companyId, companyWebsite, and companyDescription). In standard mode, all fields are always present — unavailable data points are returned as null, never omitted. In compact mode, only core fields are returned.

Enable detail enrichment in the input to get richer fields such as full descriptions and company metadata where the source provides them.

Input

The main inputs are a search keyword, an optional location filter, and a result limit. Additional filters and options are available in the input schema.

Key parameters:

  • keyword — Job search keyword (e.g. 'python developer', 'data analyst'). Not required if jobIds is provided.
  • skills — Filter by skill names (e.g. ['Python', 'Django', 'AWS']). Appended to the search keyword for server-side matching.
  • jobIds — Fetch specific jobs by their Naukri job IDs (skips keyword search). Each ID is fetched individually.
  • location — Filter by location (e.g. 'Bangalore', 'Mumbai', 'Delhi')
  • maxResults — Maximum number of jobs to return (0 = unlimited) (default: 25)
  • fetchDetails — Fetch full job details. Enables: description, roleCategory, functionalArea, jobRole, employmentType, educationUG, educationPG, applyCount, vacancy, workMode, companyDescription, companyWebsite. Slower — one extra request per job. (default: false)
  • incremental — Only return new or changed jobs since last run (state scoped per keyword+location) (default: false)
  • stateKey — Override the incremental state key. By default scoped to keyword+location. Use this to isolate state for different workflows using the same query.
  • skipReposts — Exclude listings detected as reposts of previously seen jobs. (default: false)
  • emitUnchanged — Incremental only — also emit jobs that are still in the SERP but whose tracked content has not changed since last run. (default: false)
  • emitExpired — Incremental only — also emit jobs that were present last run but are gone this run (marks them as EXPIRED). (default: false)
  • compact — Return only core fields (jobId, title, company, location, salary, experience, skills, createdDate, portalUrl, description). Ideal for AI agents and MCP workflows. (default: false)
  • ...and 13 more parameters

Input examples

Basic search — Keyword-driven search with a result cap.

→ Full payload per result — all standard fields populated where the source provides them.

{
"keyword": "python developer",
"maxResults": 50
}

Filtered search — Narrow results with advanced filters — only matching jobs are returned.

→ Same field set as basic search; fewer, more relevant rows.

{
"keyword": "python developer",
"workMode": "office",
"maxResults": 100
}

Incremental tracking — Only emit jobs that changed since the previous run with this stateKey.

→ First run builds the baseline state. Subsequent runs emit only records that are new or whose tracked content changed. Set emitUnchanged: true to include unchanged records as well.

{
"keyword": "python developer",
"maxResults": 200,
"incremental": true,
"stateKey": "python-developer-tracker"
}

Compact filtered output — Combine filters with compact mode for a lightweight AI-agent or MCP data source.

→ Core fields only — ideal for piping into LLMs or downstream tools without token overhead.

{
"keyword": "python developer",
"workMode": "office",
"maxResults": 50,
"compact": true
}

Output

Each run produces a dataset of structured job records. Results can be downloaded as JSON, CSV, or Excel from the Dataset tab in Apify Console.

Example job record

{
"jobId": "100426916818",
"title": "Custom Software Engineer",
"companyName": "Accenture",
"companyId": 27117,
"experienceText": "0-1 Yrs",
"minimumExperience": 0,
"maximumExperience": 1,
"salary": "Not disclosed",
"salaryMin": null,
"salaryMax": null,
"salaryCurrency": null,
"location": "Chennai",
"skills": [
"software engineer",
"kubernetes",
"rest",
"restful",
"load balancing",
"api gateway",
"hibernate",
"redis"
],
"createdDate": "2026-04-10T10:28:15.508Z",
"portalUrl": "https://www.naukri.com/job-listings-custom-software-engineer-accenture-solutions-pvt-ltd-chennai-0-to-1-years-100426916818",
"logoPath": "https://img.naukimg.com/logo_images/groups/v1/10476.gif",
"industry": "IT Services & Consulting",
"viewCount": 2366,
"companyWebsite": null,
"ambitionBox": {
"url": "https://www.ambitionbox.com/reviews/accenture-reviews?utm_campaign=srp_ratings&utm_medium=desktop&utm_source=naukri",
"rating": "3.7",
"reviewsCount": 73082
},
"description": "Project Role : Custom Software Engineer Project Role Description : Analyze, design, code and test multiple components of application code across one or more clients. Perform maintenance, enhancements...",
"descriptionHtml": "<b>Project Role :</b>Custom Software Engineer<br /><b><br /><br />Project Role Description :</b>Analyze, design, code and test multiple components of application code across one or more clients. Perfo...",
"descriptionMarkdown": "**Project Role :**Custom Software Engineer\n**Project Role Description :**Analyze, design, code and test multiple components of application code across one or more clients. Perform maintenance, enhance...",
"roleCategory": "Software Development",
"functionalArea": "Engineering - Software & QA",
"jobRole": "Search Engineer",
"employmentType": "Full Time, Permanent",
"educationUG": [
"B.Tech / B.E. in Any Specialization"
],
"educationPG": [
"Any Postgraduate"
],
"applyCount": 719,
"vacancy": 0,
"wfhType": "office",
"companyDescription": "About Accenture<br><br> <br><br>Accenture is a global professional services company with leading capabilities in digital, cloud and security. Combining unmatched experience and specialized skills acro...",
"scrapedAt": "2026-04-12T21:21:18.505Z",
"searchKeyword": "software engineer"
}

In compact mode, output is reduced to core fields: jobId, title, companyName, location, salary, experienceText, skills, createdDate, and portalUrl.

Incremental fields

When incremental: true, each record also carries:

  • changeType — one of NEW, UPDATED, UNCHANGED, REAPPEARED, EXPIRED. Default output covers NEW / UPDATED / REAPPEARED; set emitUnchanged: true or emitExpired: true to opt into the others.
  • firstSeenAt, lastSeenAt — ISO-8601 timestamps tracking the listing across runs.
  • isRepost, repostOfId, repostDetectedAt — populated when a new listing matches the tracked content of a previously expired one. Set skipReposts: true to drop detected reposts from the output.

How to scrape naukrigulf.com

  1. Go to Naukri.com Job Scraper in Apify Console.
  2. Enter a search keyword and optional location filter.
  3. Set maxResults to control how many results you need.
  4. Enable includeDetails if you need full descriptions, contact info, or company data.
  5. Click Start and wait for the run to finish.
  6. Export the dataset as JSON, CSV, or Excel.

Use cases

  • Extract job data from naukrigulf.com for market research and competitive analysis.
  • Track salary trends across regions and categories over time.
  • Monitor new and changed listings on scheduled runs without processing the full dataset every time.
  • Build outreach lists using contact details and apply URLs from listings.
  • Research company hiring patterns, employer profiles, and industry distribution.
  • Feed structured data into AI agents, MCP tools, and automated pipelines using compact mode.
  • Export clean, structured data to dashboards, spreadsheets, or data warehouses.
  • Analyze skill demand across listings using structured skill tags.

How much does it cost to scrape naukrigulf.com?

Naukri.com Job Scraper uses pay-per-event pricing. You pay a small fee when the run starts and then for each result that is actually produced.

  • Run start: $0.01 per run
  • Per result: $0.002 per job record

Example costs:

  • 10 results: $0.03
  • 100 results: $0.21
  • 500 results: $1.01

Example: recurring monitoring savings

These examples compare full re-scrapes with incremental runs at different churn rates. Churn is the share of listings that are new or whose tracked content changed since the previous run. Actual churn depends on your query breadth, source activity, and polling frequency — the scenarios below are examples, not predictions.

Example setup: 100 results per run, daily polling (30 runs/month). Event-pricing examples scale linearly with result count.

Churn rateFull re-scrape run costIncremental run costSavings vs full re-scrapeMonthly cost after baseline
5% — stable niche query$0.21$0.02$0.19 (90%)$0.60
15% — moderate broad query$0.21$0.04$0.17 (81%)$1.20
30% — high-volume aggregator$0.21$0.07$0.14 (67%)$2.10

Full re-scrape monthly cost at daily polling: $6.30. First month with incremental costs $0.79 / $1.37 / $2.24 for the 5% / 15% / 30% scenarios because the first run builds baseline state at full cost before incremental savings apply.

FAQ

How many results can I get from naukrigulf.com?

The number of results depends on the search query and available listings on naukrigulf.com. Use the maxResults parameter to control how many results are returned per run.

Does Naukri.com Job Scraper support recurring monitoring?

Yes. Enable incremental mode to only receive new or changed listings on subsequent runs. This is ideal for scheduled monitoring where you want to track changes over time without re-processing the full dataset.

Can I integrate Naukri.com Job Scraper with other apps?

Yes. Naukri.com Job Scraper works with Apify's integrations to connect with tools like Zapier, Make, Google Sheets, Slack, and more. You can also use webhooks to trigger actions when a run completes.

Can I use Naukri.com Job Scraper with the Apify API?

Yes. You can start runs, manage inputs, and retrieve results programmatically through the Apify API. Client libraries are available for JavaScript, Python, and other languages.

Can I use Naukri.com Job Scraper through an MCP Server?

Yes. Apify provides an MCP Server that lets AI assistants and agents call this actor directly. Use compact mode and descriptionMaxLength to keep payloads manageable for LLM context windows.

This actor extracts publicly available data from naukrigulf.com. Web scraping of public information is generally considered legal, but you should always review the target site's terms of service and ensure your use case complies with applicable laws and regulations, including GDPR where relevant.

Your feedback

If you have questions, need a feature, or found a bug, please open an issue on the actor's page in Apify Console. Your feedback helps us improve.

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