💼 Naukri & AmbitionBox Jobs Scraper

Collect fresh India job listings from Naukri and turn them into clean recruiting intelligence: roles, companies, locations, salaries, skills, experience ranges, full job details, and AmbitionBox company context when it is available.

Use it for recruiting research, job-board datasets, salary tracking, skills analysis, staffing lead generation, and India hiring-market monitoring.

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✨ What you get

Data	Description
🧑‍💻 Fresh jobs	Job title, company, job ID, Naukri URL, posted date, location, experience, and salary text.
🧠 Skills	Skills and keywords from Naukri search cards or full job details.
💰 Salary signals	Salary label, numeric salary fields when Naukri exposes them, and salary lines extracted from detailed descriptions when available.
🏢 Company context	Company name, company ID, logo, profile text, and company jobs URL.
⭐ AmbitionBox data	Rating, review count, and company context when Naukri includes AmbitionBox blocks.
📄 Detailed mode	Full job description, education, role category, employment type, and richer company fields.

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🚀 Quick start

1. Choose a keyword, for example data engineer.
2. Add one or more cities, for example Bengaluru.
3. Set maxJobs.
4. Keep fetchDetails off for fast search-card exports, or turn it on for full job intelligence.
5. Run the actor and open the Jobs output tab.

Default first run:

{
  "keyword": "data engineer",
  "cities": ["Bengaluru"],
  "maxJobs": 100,
  "fetchDetails": false
}

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🧭 Input modes

Mode	Best for	How to use
Keyword + city	Broad job discovery	Fill keyword, cities, and optional filters.
Search URL	Reusing exact filters from Naukri	Paste a full Naukri results URL into searchUrl.
Direct job IDs	Exact known vacancies	Add IDs to jobIds; search filters are ignored.

Priority is simple:

jobIds -> searchUrl -> keyword + filters

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📥 Input examples

Fresh data engineer jobs in Bengaluru

{
  "keyword": "data engineer",
  "cities": ["Bengaluru"],
  "freshness": "7",
  "sortBy": "date",
  "maxJobs": 100
}

Detailed India recruiting intelligence

{
  "keyword": "product manager",
  "cities": ["Mumbai", "Bengaluru"],
  "freshness": "30",
  "maxJobs": 100,
  "fetchDetails": true
}

Salary and experience research

{
  "keyword": "devops engineer",
  "cities": ["Pune"],
  "experience": "3-7",
  "salaryRange": ["15to25", "25to50"],
  "maxJobs": 200
}

Use a Naukri search URL

{
  "searchUrl": "https://www.naukri.com/python-developer-jobs-in-bengaluru?k=python%20developer&l=bengaluru",
  "maxJobs": 100
}

Fetch exact job IDs

{
  "jobIds": ["220126040161", "170424007054"],
  "maxJobs": 50,
  "fetchDetails": true
}

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🎛️ Main input fields

Field	Description
keyword	Role, skill, or job title to search.
cities	City names or numeric Naukri city IDs.
maxJobs	Maximum jobs to save. Minimum safe value is 50.
fetchDetails	Adds full descriptions, skills, company profiles, and AmbitionBox context.
searchUrl	Full Naukri search-results URL with filters already applied.
jobIds	Exact job IDs to fetch directly.
freshness	1, 3, 7, 15, 30, or all.
sortBy	relevance or date.
experience	Experience filter such as 2, 5, or 3-7.
salaryRange	Salary buckets such as 10to15, 15to25, or 75plus.
industry	Numeric Naukri industry IDs.

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📊 Output views

The actor writes clean rows into the default Apify dataset. The Output tab opens on Jobs, so users immediately see the collected vacancies.

View	Purpose	Typical fields
Jobs	Fast export for job listings	jobId, title, companyName, location, experience, salary, salarySource, skills, url
Recruiting intelligence	Salary, skills, and hiring-market analysis	salary fields, salary source, skills, AmbitionBox object, posted date
Companies & AmbitionBox	Company-level context	company ID, company slug, profile, logo, AmbitionBox data
Errors	Clean non-fatal notices	error type, message, input context

You can export every view to JSON, CSV, Excel, XML, RSS, Google Sheets, Make, Zapier, n8n, or your own API.

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🧾 Example output item

{
  "jobId": "220126040161",
  "title": "Senior Data Engineer",
  "companyName": "Example Analytics",
  "location": "Bengaluru",
  "experience": "5-10 Yrs",
  "salary": "18K to 25K",
  "salarySource": "job_description",
  "tagsAndSkills": ["Python", "Spark", "SQL"],
  "currency": "INR",
  "createdDate": "2026-07-06",
  "jdURL": "https://www.naukri.com/job-listings-...",
  "ambitionBoxData": {
    "AggregateRating": "4.1",
    "ReviewsCount": 1240
  }
}

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🧩 Recommended workflows

Recruiter sourcing

Run keyword + city searches every day with sortBy: "date" and freshness: "1" to track newly posted roles.

Salary and skills research

Use salary buckets, experience filters, and the Recruiting intelligence view to compare demand across cities and seniority levels.

Company hiring intelligence

Turn on fetchDetails and use Companies & AmbitionBox to collect company profiles, job URLs, and AmbitionBox context in one dataset.

Exact vacancy enrichment

Use jobIds when you already have Naukri job IDs and need detailed records for those exact postings.

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✅ Data quality notes

• salary: "Not disclosed" means the employer did not publish a salary on Naukri.
• In fetchDetails: true mode, the actor also looks for salary lines inside the job description, for example Salary: 18K to 25K.
• AmbitionBox fields appear only when Naukri includes them for that company or job.
• Some company profile fields are richer in fetchDetails: true mode.
• The actor removes empty internal fields before saving results, so the dataset stays clean.
• If Naukri returns a temporary empty/protected response before any job is collected, the actor finishes cleanly with an Errors row instead of marking the run as failed.

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❓ FAQ

Do I need a Naukri account or API key?
No. The actor collects public job data.

Which mode should I use first?
Start with keyword + city. Use searchUrl when you want to reproduce filters from Naukri, and jobIds when you need exact postings.

Why is the minimum maxJobs 50?
Naukri returns jobs in paginated batches. You can still export or use only the first rows you need.

Why are some salary or company fields missing?
Those values are not public for every job. This is normal for Naukri and AmbitionBox data.

When should I turn on fetchDetails?
Use it when you need full job descriptions, education, role/category data, or richer company context. Keep it off for faster bulk searches.

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🏷️ Tags

naukri scraper · naukri jobs · ambitionbox data · india jobs scraper · recruiting intelligence · job board scraper · salary research · skills analytics · hr tech · staffing leads