Naukri Job Scraper — Clean JSON for India's Largest Job Board

Turn Naukri.com job listings into clean, structured JSON you can drop straight into a spreadsheet, database, or CRM. Search by keyword with rich filters, or pull specific job IDs — and optionally enrich every job with its full description, live applicant count, deep skill list, education requirements, and company profile.

Unlike scrapers that dump the raw, deeply-nested API response, this actor emits a flat, one-level, documented row per job. It runs on Naukri's mobile API backend, which has no browser anti-bot challenge — so it stays reliable at scale.

Who uses this

• Recruiters & talent-market analysts — track job volume, salary bands, and in-demand skills by role, city, and company.
• HR-tech / job-board developers — ingest a stable JSON schema into your app, no HTML parsing, no nested-envelope wrangling.
• Labor-market researchers — measure hiring velocity, skills frequency, and applicant competition (apply_count) across the Indian market.

Output fields

Field	Type	Description
job_id	string	Naukri job ID
title	string	Job title
job_url	string	Canonical job page URL
company_name	string	Hiring company
company_id / group_id	number	Company & group identifiers
posted_date	ISO 8601	When the job was posted
posted_label	string	Human label (e.g. "1 Day Ago")
experience_text / experience_min / experience_max	string / int	Experience required
salary_min / salary_max / salary_currency / salary_label / salary_disclosed	mixed	Salary band (often undisclosed on Naukri)
work_mode	string	Work from office / Remote / Hybrid
locations	array	Job locations
skills	array	Required skills
job_role / role_category / functional_area / industry	string	Role taxonomy (details mode)
employment_type	string	Full-time / contract etc. (details mode)
vacancy	number	Openings (details mode)
apply_count	number	Live applicant count (details mode)
view_count	number	Job views (details mode)
walk_in	boolean	Walk-in interview flag (details mode)
company_rating / company_reviews_count	number	AmbitionBox rating & reviews
company_website	string	Company site (details mode)
education_ug / education_pg	array	Education requirements (details mode)
short_description / description_text / description_html	string	Job description (plain + HTML)
logo_url	string	Company logo
is_detailed	boolean	Whether the row was detail-enriched
scraped_at	ISO 8601	Scrape timestamp

Fields marked (details mode) are populated when Include full job details is on, or when a job is fetched by ID.

High-value use cases

• Skills-demand dashboards — aggregate skills across thousands of postings to see which frameworks and tools are hiring.
• Salary & compensation benchmarking — group salary_* by role_category and locations for market comp reports.
• Competitive hiring intelligence — track a competitor's openings via company_id, including how many applicants each role attracts (apply_count).
• Sourcing pipelines — feed fresh, filtered job rows (by workMode, jobAge, experience) into your ATS or lead tools.
• Academic labor-market research — reproducible, structured snapshots of the Indian job market over time.

Input parameters

Field	Type	Default	Description
keywords	array	["python developer"]	Titles, skills or companies to search
location	string	—	City, e.g. bangalore
maxItems	integer	100	Cap across all keywords (0 = unlimited)
includeDetails	boolean	false	Fetch full detail per job
workMode	enum	any	office / remote / hybrid
sortBy	enum	relevance	relevance / date / recommended
experience	integer	—	Years of experience
jobAge	integer	—	Posted within N days
salaryRange	string	—	Salary bucket, e.g. 6to10
resultsPerPage	integer	100	Page size (max 100)
jobIds	array	—	Fetch exact job IDs (always detailed)
proxyConfiguration	object	none	Optional Apify proxy

Example input

{
  "keywords": ["data scientist", "machine learning"],
  "location": "bangalore",
  "maxItems": 200,
  "includeDetails": true,
  "workMode": "hybrid",
  "sortBy": "date",
  "jobAge": 7
}

Example output (one row)

{
  "job_id": "070926918037",
  "title": "Python Developer",
  "company_name": "Appscrip",
  "locations": ["Bengaluru"],
  "experience_text": "0-1 Yrs",
  "salary_label": "Not disclosed",
  "work_mode": "Work from office",
  "skills": ["python", "fastapi", "django", "rest"],
  "apply_count": 1483,
  "role_category": "Software Development",
  "company_rating": 2.6,
  "posted_date": "2026-09-07T10:49:02+00:00",
  "job_url": "https://www.naukri.com/job-listings-python-developer-appscrip-bengaluru-0-to-1-years-070926918037",
  "is_detailed": true,
  "scraped_at": "2026-09-08T00:00:00+00:00"
}

Scheduling & integrations

• Schedule runs (hourly/daily) from the Apify Console to keep a fresh job feed.
• Webhooks — trigger a downstream service when a run finishes.
• Export to JSON, CSV, Excel, or push to Google Sheets, Make, Zapier, or S3.
• The dataset is available via Apify's API for direct ingestion.

Use it from an AI assistant (MCP)

This actor works with the Apify MCP server, so AI agents (Claude, ChatGPT, or any MCP client) can call it as a tool — e.g. "find remote data-scientist jobs in Bangalore posted this week" — and receive structured rows back.

FAQ

How many jobs can I scrape? As many as the search returns — set maxItems: 0 for unlimited. Naukri search paginates reliably to thousands of results per query.

How fresh is the data? Live. Every run hits Naukri's API in real time; use sortBy: date and jobAge for the newest postings.

Why are some salaries empty? Most Indian employers mark salary "Not disclosed" on Naukri; salary_disclosed tells you which rows have real figures.

Listing vs details mode? Listing mode (default) is fast and cheap — search results already include title, company, salary, skills and a short description. Turn on Include full job details for apply counts, education, deep skills and company profiles (one extra request per job).

Is it reliable? The actor uses Naukri's mobile API backend, which has no browser anti-bot challenge, so it doesn't break the way HTML/web scrapers do when the site changes.

Is scraping this legal? The actor collects only publicly available job listings. You are responsible for using the data in line with Naukri's terms and applicable laws (e.g. GDPR) in your jurisdiction.

Support? Issues are monitored and typically answered within 24 hours.