Shine.com Jobs Scraper
Pricing
from $1.60 / 1,000 shine.com jobs scrapers
Shine.com Jobs Scraper
Collect public job listings from Shine in India. Get titles, companies, locations, salary, experience, skills and dates. Use keywords, Indian cities or public Shine job-search URLs; no Shine login. Pricing: $0.0016/item + $0.00005/Actor Start.
Pricing
from $1.60 / 1,000 shine.com jobs scrapers
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Vitalii Bondarev
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3 days ago
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Scrape public Shine.com job listings in India from server-rendered search results. Start with keywords or public Shine job-search URLs; no Shine login is used, and detail-page fields are optional. Price on the Free plan: $0.0016 per result plus $0.00005 per start event. The default input uses Apify Residential proxy.
- Extract titles, companies, locations, salary, experience, skills, dates and public URLs
- Build recruiting research and hiring-data feeds
- Search by keyword and Indian city, or use public Shine job-search URLs
- Open public detail pages for descriptions, industry, employment type and expiry dates
- Deduplicate by Shine job ID within a run
What you get
| Field | Type | What it contains |
|---|---|---|
jobId | string | Shine job ID. |
title | string | Job title. |
company | string | Employer name. |
companyId | integer | Shine company ID. |
url | string | Public Shine job detail URL. |
locations | array of strings | Listing locations. |
location | string | Locations joined into one string. |
salaryText | string | Salary exactly as listed. |
salaryMinLakh | number | Minimum salary normalized to lakh/year for recognized rupee, lakh or crore amounts. |
salaryMaxLakh | number | Maximum salary normalized to lakh/year for recognized rupee, lakh or crore amounts. |
salaryPeriod | string | Recognized period such as month or year. |
experienceText | string | Experience requirement as listed. |
experienceMinYears | number | Parsed minimum experience in years. |
experienceMaxYears | number | Parsed maximum experience in years. |
skills | array of strings | Skills from search or detail data. |
badges | array of strings | Shine badges. |
postedAt | ISO 8601 string | Posting timestamp in UTC. |
expiresAt | ISO 8601 string | Expiry timestamp in UTC. |
employmentType | string | Employment type from public detail data. |
industry | string | Industry from public detail data. |
descriptionText | string | Plain-text description; email addresses and Indian phone-number patterns are replaced with [contact removed]. |
searchKeyword | string | Keyword used for the search. |
searchLocation | string | City used for the search. |
sourcePage | string | Shine search page producing the record. |
scrapedAt | ISO 8601 string | Collection time in UTC. |
Sample output
The sample below is shortened by omitting only the long descriptionText field. All other values are copied from one real dataset record.
{"jobId": "19543510", "title": "Aicess India - Operations Executive (Greater Noida)","url": "https://www.shine.com/jobs/aicess-india-operations-executive-greater-noida/korea-trade-investment-promotion-kotra/19543510","company": "Korea Trade Investment Promotion (KOTRA)", "companyId": 769865,"locations": ["Noida"], "location": "Noida","salaryText": "Not Disclosed","experienceText": "0 to 4 Yrs", "experienceMinYears": 0, "experienceMaxYears": 4,"skills": ["Office Administration", "Documentation", "Record Keeping", "Statutory Compliance", "Incorporation", "Registration", "Internal Processes", "Amendment Procedures"],"postedAt": "2026-09-07T13:16:25Z", "expiresAt": "2026-11-06T13:16:22Z","employmentType": "FULL_TIME", "industry": "IT Services & Consulting","searchKeyword": "jobs in all india","sourcePage": "https://www.shine.com/job-search/jobs-in-all-india","scrapedAt": "2026-10-18T08:15:29.818637Z"}
Pricing
You pay only for the events listed below. This Actor does not use the Pay per event + usage option, so the platform usage of your runs (compute, proxy traffic and storage) is not billed to you separately.
The Actor charges two pay-per-event events:
| Charge event | Free-plan price | Unit and condition |
|---|---|---|
apify-default-dataset-item | $0.0016 per event on Free | One event for each scraped result with all fields. |
apify-actor-start | $0.00005 per event on Free | One event per GB of run memory, minimum one event. |
For a run with 1 GB of memory or less (one start event):
| Results | Dataset items | Start event | Total on Free |
|---|---|---|---|
| 10 | 10 × $0.0016 per dataset item | $0.00005 per start event | $0.01605 |
| 1,000 | 1,000 × $0.0016 per dataset item | $0.00005 per start event | $1.60005 |
| 10,000 | 10,000 × $0.0016 per dataset item | $0.00005 per start event | $16.00005 |
How to use
- Fill
keywordsandlocations(orsearchUrls) and setmaxResults; see Input parameters below. - Run the Actor and inspect the dataset.
- Repeat the run through Apify Schedules. Deduplication and
maxResultsapply within one run only, so scheduled runs can return the same listings again.
{"keywords": ["python developer"],"locations": [],"searchUrls": [],"maxResults": 10,"includeDescription": true,"proxyConfiguration": {"useApifyProxy": true, "apifyProxyGroups": ["RESIDENTIAL"]}}
Export the dataset as JSON or CSV, or read it through the Apify dataset API.
Input parameters
| Parameter | What it does | Default |
|---|---|---|
keywords | Search phrases, job titles or skills combined with every city in locations. | ["jobs in all india"] |
locations | Optional Indian cities. An empty list means all India. | [] |
searchUrls | HTTPS Shine /job-search/ URLs replacing keyword searches when non-empty; only pages without query strings are accepted. | [] |
maxResults | Maximum total unique listings written across searches. The schema requires an integer of at least 1. | 50 |
includeDescription | Opens each public detail page for description, industry, employment type and expiry date. | true |
proxyConfiguration | Apify proxy settings. | {"useApifyProxy": true, "apifyProxyGroups": ["RESIDENTIAL"]} |
Limits and edge cases
| Condition | What the buyer sees | What to do |
|---|---|---|
maxResults is reached | Collection stops at that many unique records in the run. | Increase maxResults. |
| More than 50 generated or supplied searches are available | Only the first 50 unique search URLs are read. | Narrow combinations or provide relevant URLs. |
| A search has more than 250 pages | That search stops at the supported page limit. | Narrow or split the search. |
| A search request fails (after one retry for some errors) | That search ends with a warning and later searches continue; the run can finish with fewer or zero results. | Rerun later or try another keyword, city or URL. |
A supplied URL is not an HTTPS Shine /job-search/ page, or has a query string or fragment | It is skipped; if none remain, the run warns and returns without records. | Use a valid public Shine job-search URL without a query string or fragment. |
A detail-page request fails with includeDescription enabled | The listing can still be written with search-page fields; detail fields may be absent and a warning is logged. | Rerun or disable detail-page collection. |
| Salary is hidden, confidential, undisclosed, or lacks a recognized rupee, lakh or crore unit | salaryText may remain, but normalized salary fields are not inferred. | Use salaryText; do not treat missing numbers as zero. |
| The description contains an email address or Indian phone number | Matching patterns are replaced with [contact removed] in descriptionText; other contact details may remain. | Review the description before reuse. |
FAQ
How much does it cost to scrape Shine.com jobs?
See the Pricing section for Free-plan event prices and examples.
Why did my run return no jobs?
Check the run log for the reason, and confirm that keywords, locations and searchUrls are valid.
What should I do if the Actor does not work?
Use arrays for keywords, locations and searchUrls, set maxResults to at least 1, and provide public HTTPS Shine job-search pages without query strings.
Is it legal or allowed to collect and use these listings?
The Actor collects public job-listing data from Shine.com. Whether collection or use is legal or allowed depends on the source terms, applicable law and your use case; review those requirements before using the data.
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