Apna.co Jobs Scraper: Blue and Grey Collar Vacancies

Get instant, structured access to blue-collar and grey-collar job listings in India. Extract verified salary ranges, direct call or WhatsApp recruiter preferences, and coordinate mappings in bulk.

What does Apna.co Jobs Scraper do?

The Apna.co Jobs Scraper is a high-speed web scraping tool that extracts complete grey-collar and blue-collar job listings from Apna (apna.co), India's leading employment platform.

It is built for developers, recruitment boards, job aggregators, and sales lead-generation teams. By loading Apna's Next.js pre-rendered pages, it parses the server-side hydration state JSON from the __NEXT_DATA__ script tag directly.

This means a single page request harvests 25 complete, detailed job listings (including descriptions, physical addresses, coordinate points, and direct call/WhatsApp HR contact preferences). You do not need to request individual job detailed pages, which reduces HTTP overhead by 96% and keeps your running cost extremely low.

With Apify, you can automate this scraper using a simple REST API, schedule runs daily to track fresh listings, and automatically integrate datasets with Google Sheets, Airtable, Make, or webhooks.

Why use Apna.co Jobs Scraper?

• Find Direct Recruiter Leads: Filter for companies actively hiring at scale and see if they accept direct phone calls or WhatsApp messages. Perfect for B2B recruiting outreach and sales prospecting.
• Benchmark Blue & Grey-Collar Compensation: Compare minimum and maximum salary ranges across categories, departments, and cities to build accurate compensation datasets.
• Track Hiring Gaps: Monitor which roles are trending in specific municipal regions (e.g. Bengaluru, Mumbai, Delhi) to capture economic hiring demand shifts.
• Deduplicated Job Feeds: Feed your career dashboard, counselor portal, or job board with clean, normalized listings complete with direct application links.

How to use Apna.co Jobs Scraper

1. Set Up: Open the Apna.co Jobs Scraper in the Apify Console.
2. Configure Input: Enter a search keyword (e.g., telecalling_bpo_telesales) and location (e.g., Mumbai/Bombay), or enter a direct search url.
3. Limit Results: Define maxItems to restrict dataset records and manage budgets.
4. Run: Click the Start button. Once finished, download your structured job records as JSON, CSV, Excel, or HTML from the Output tab.

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Input Parameters

The scraper accepts these input configuration settings:

Field	Type	Description	Default
url	String	Direct search URL to crawl. Overrides keyword and location.	""
keyword	String	Search role, category, or title keyword (e.g. "delivery_person", "back_office").	"software engineer"
location	String	Target city exactly as named on Apna (e.g. "Bengaluru/Bangalore", "Mumbai/Bombay").	"Bengaluru/Bangalore"
maxItems	Integer	Maximum number of job records to collect.	100
dateWithinDays	Integer	Only include vacancies posted within the last N days (0 = any time).	0
maxConcurrency	Integer	Maximum parallel page requests.	8
proxyConfiguration	Object	Proxy routing settings. Datacenter proxies are fully supported.	{"useApifyProxy": false}

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Output Structure

The scraper outputs fully normalized flat job rows with empty fields omitted. Here is a sample JSON representation:

{
  "job_id": 795315922,
  "title": "Customer Service Executive",
  "description_text": "HIRING – INTERNATIONAL BPO | CUSTOMER SERVICE (MUMBAI)\n\nContact Heren Bhagchandani - HR lead - 8928056592\nSalary: ₹20K – ₹70K + Attractive Incentives...",
  "company": "Conviction Hr Private Limited",
  "url": "https://apna.co/job/mumbai-bombay/customer-service-executive-795315922",
  "location": "Malad West, Mumbai/Bombay",
  "city": "Mumbai",
  "category": "Telecalling / BPO / Telesales",
  "department_name": "Customer Support",
  "min_salary": 18000,
  "max_salary": 110000,
  "experience_in_years": "Freshers can apply",
  "no_of_openings": 10,
  "job_address_line_1": "1406/11, Chincholi Bunder Rd, Malad, Ram Nagar, Malad West, Mumbai, Maharashtra 400064, India",
  "job_address_area": "Quinscent Height",
  "job_address_city": "Mumbai",
  "company_address_line_1": "1406/11, Chincholi Bunder Rd, Malad, Ram Nagar, Malad West, Mumbai, Maharashtra 400064, India",
  "company_address_area": "Quinscent Height",
  "company_address_city": "Mumbai",
  "whatsapp_accepted": true,
  "call_accepted": true,
  "created_on": "2026-06-04T00:00:00.000+00:00",
  "expiry": "2026-06-19",
  "ui_tags": [
    "Work from Office",
    "Full Time",
    "Any experience",
    "Good (Intermediate / Advanced) English"
  ],
  "scraped_at": "2026-06-07T06:53:39.815Z"
}

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Output Fields Explanation

Field Name	Type	Description
job_id	Number	Unique identifier for the Apna.co vacancy posting.
title	String	Job position title.
description_text	String	Plain-text job description content.
company	String	Hiring organization name.
logo_url	String	Hiring organization logo URL.
url	String	Link to the original posting.
location	String	Main display location name.
city	String	Primary city.
category	String	Job category.
department_name	String	Job department name.
min_salary	Number	Minimum salary value.
max_salary	Number	Maximum salary value.
experience_in_years	String	Experience requirements summary label.
no_of_openings	Number	Number of openings.
work_mode	String	Work shift or location policies.
job_address_line_1	String	Flattened job address.
job_address_area	String	Flattened job area.
job_address_city	String	Flattened job city.
company_address_line_1	String	Flattened company address.
company_address_area	String	Flattened company area.
company_address_city	String	Flattened company city.
whatsapp_accepted	Boolean	Whether the employer accepts direct WhatsApp messages.
call_accepted	Boolean	Whether the employer accepts direct phone calls.
created_on	String	ISO formatted publication date.
expiry	String	Expiration date of the job posting.
ui_tags	Array	List of tags shown on the UI.
scraped_at	String	Scraping execution timestamp.

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Cost Estimation & Pricing

Because this Actor utilizes Next.js state harvesting, a single page request harvests 25 complete, detailed records. No dynamic browser rendering (Playwright/Puppeteer) is required, which dramatically reduces memory and CPU overhead.

• Standard platform rate: $1.99 per 1,000 results (excludes micro platform execution fees).
• Scraping 5,000 detailed jobs requires only 200 HTTP page requests, costing approximately $9.95 in bandwidth and compute combined.

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FAQ, Disclaimers, and Support

• Is scraping Apna.co legal? Yes. This scraper extracts publicly visible job postings published by employers looking to attract applicants. It does not access private candidate profiles or personal account pages. Use the collected data in compliance with local privacy laws and respect server bandwidth by setting sensible concurrency limits.
• Do I need residential proxies? For small-scale runs (under 5,000 jobs), standard datacenter proxies or no proxy will work cleanly. For continuous, high-volume production crawls, residential proxies may be helpful.
• Can I run this on a schedule? Yes. Create a Schedule in the Apify Console to run the scraper daily, weekly, or monthly.
• How can I suggest features or report bugs? Open an issue in the Issues tab on this Actor's page, or contact us through the Apify Console.