Jobstreet Jobs Search Scraper

JobStreet.com Jobs Search Scraper: Extract Singapore & Southeast Asia Job Market Data

Understanding JobStreet.com and Its Regional Significance

JobStreet.com stands as Southeast Asia's most prominent online recruitment platform, serving millions of job seekers and employers across Singapore, Malaysia, Philippines, Indonesia, Thailand, and Vietnam. Unlike Western-focused job boards, JobStreet.com specializes in the unique dynamics of Asian employment markets, including diverse work visa requirements, regional salary expectations, and local labor regulations.

The platform's importance in the region cannot be overstated. For Singapore alone, JobStreet.com hosts thousands of active listings spanning finance, technology, healthcare, logistics, and manufacturing sectors. The data available through these listings provides unparalleled insights into hiring trends, salary benchmarks, skill requirements, and company expansion patterns across one of the world's most dynamic economic regions.

However, gathering this information manually across multiple search pages, categories, and locations would require enormous time investment. The JobStreet.com Jobs Search Scraper automates this process, enabling you to collect structured data from search results pages efficiently, whether you're analyzing ten positions or ten thousand across the entire Southeast Asian market.

What This Scraper Delivers and Target Users

The JobStreet.com Jobs Search Scraper extracts comprehensive information from job search result pages rather than individual job detail pages. This approach allows you to quickly gather broad market overviews, identify hiring patterns, and build extensive job databases without needing to visit each individual listing.

The scraper captures all key information displayed in search results, including job titles, employer details, locations, work arrangements (remote, hybrid, on-site), classifications (industry categories), salary information when disclosed, and branding elements that indicate featured or premium listings. This provides an efficient snapshot of the job market without the overhead of deep scraping individual pages.

This tool serves multiple professional needs effectively. Recruitment agencies can monitor competitor activity, identify high-volume hiring companies, and spot emerging job categories. Market analysts gain visibility into regional employment trends, salary disclosure practices, and geographic distribution of opportunities. Business development teams can identify expanding companies by tracking their hiring velocity. HR departments benchmark their job postings against market standards and optimize their own listings for better visibility.

Input Configuration and Requirements Explained

The scraper accepts JobStreet.com search result page URLs, which are the pages you see after performing a search on the platform. These URLs typically contain search parameters like keywords, locations, and pagination information. The format generally follows: https://[country].jobstreet.com/[keyword]-jobs?page=[number].

Here's a detailed breakdown of the input configuration:

{
  "proxy": {
    "useApifyProxy": true,
    "apifyProxyGroups": [
    "RESIDENTIAL"
    ],
    "apifyProxyCountry": "SG"
  },
  "max_items_per_url": 20,
  "ignore_url_failures": true,
  "urls": [
    "https://sg.jobstreet.com/audit-jobs?page=2"
  ]
}

Example Screenshot:

Proxy Configuration: The useApifyProxy setting determines whether to route requests through Apify's proxy network. While set to false in this example, enabling proxies (true) is recommended for larger scraping operations to prevent rate limiting or IP blocking, especially when collecting data across multiple countries or categories.

Max Items Per URL: This parameter controls how many job listings to extract from each search page URL. JobStreet.com typically displays 20-30 results per page, so setting this to 20 ensures you capture most visible listings without overloading requests. Adjust this based on your needs—lower values for quick sampling, higher for comprehensive collection.

Ignore URL Failures: When set to true, the scraper continues processing remaining URLs even if some fail due to network issues or page changes. This is crucial for large-scale operations where you don't want one problematic URL to halt the entire scraping job.

URLs Array: Include one or multiple search result page URLs. You can add various searches covering different keywords, locations, or countries. For example, combine searches for "data analyst jobs" in Singapore, "software engineer jobs" in Malaysia, and "marketing manager jobs" in Philippines within a single run.

To collect paginated results, include multiple page URLs from the same search (page=1, page=2, page=3, etc.), or the scraper may handle pagination automatically depending on your max items configuration.

Complete Output Structure and Field Definitions

The scraper returns JSON data with each job listing as an object containing detailed fields. Understanding field purposes enables effective analysis and application.

Listing Identification

ID: Unique numeric identifier of the job listing on Jobstreet. Purpose: Database indexing, tracking specific jobs over time, avoiding duplicates, linking to detail pages.

Listing URL: Direct link to the full job listing on Jobstreet. Purpose: Accessing complete details, applying for the job, verification of scraped data.

Title: Job title as posted by the employer. Purpose: Role-based filtering, keyword analysis, job market trend tracking.

Teaser: Short promotional summary of the job shown in search results. Purpose: Quick preview of the role and employer pitch.

Role ID: URL-friendly role identifier assigned by the platform. Purpose: Grouping similar roles and standardizing job titles across listings.

Bullet Points: List of key selling points highlighted by the employer (salary, benefits, work environment). Purpose: Benefits analysis, comparing employer offerings, extracting perks and incentives.

Job Classification

Classifications: List of objects describing the job's category and subcategory, each with classification_id, classification, subclassification_id and subclassification. Purpose: Industry segmentation, demand analysis per field, filtering by specialization.

Work Types: List of employment types (e.g., Full time, Part time, Contract). Purpose: Separating permanent roles from flexible or temporary positions.

Work Arrangements: List of work setup options (e.g., On-site, Hybrid, Remote). Purpose: Analyzing remote-work availability and filtering by work style.

Salary Label: Salary range exactly as displayed on the listing (may be null when not disclosed). Purpose: Compensation benchmarking, salary range filtering, pay transparency analysis.

Location

Location: Primary location label of the job. Purpose: Quick display and filtering by area.

Country Code: ISO country code of the primary location (e.g., SG). Purpose: Multi-country segmentation and market comparison.

Locations: List of objects for every job location, each with label, country_code and hierarchy (area names from most specific to broadest). Purpose: Geographic analysis at multiple levels, handling jobs with several locations.

Employer

Company Name: Name of the hiring company. Purpose: Lead generation, competitor analysis, employer hiring-activity tracking.

Employer ID: Unique identifier of the employer profile on the platform. Purpose: Grouping jobs by employer, tracking hiring volume over time.

Company Logo URL: Link to the employer's logo shown in search results. Purpose: Branding in reports and dashboards.

Advertiser ID: Unique identifier of the account that posted the job. Purpose: Distinguishing direct employers from recruitment agencies posting on their behalf.

Advertiser Name: Name of the account that posted the job. Purpose: Identifying the posting entity and detecting agency-posted jobs.

Listing Dates

Listing Date: Date and time the job was published (ISO 8601). Purpose: Measuring job freshness, time-series analysis of hiring trends.

Listing Date Display: Relative posting time as shown on the website (e.g., 6d ago). Purpose: Quick reading of freshness and verification against the website.

Listing Status

Is Featured: Whether the listing is promoted as a featured job. Purpose: Analyzing employer advertising investment and listing visibility.

Display Type: Display format of the listing in search results (e.g., standard). Purpose: Differentiating standard listings from enhanced or branded ones.

Ad Type: Type of ad placement (e.g., ORGANIC, SPONSORED). Purpose: Separating organic from paid listings.

Raw Data

Raw Data: Complete original JSON object of the job listing as scraped, without modification. Purpose: Auditing, debugging, accessing fields not included in the cleaned output, and reprocessing without re-scraping.

Here's an example of the scraped output:

{
  "id": "95642329",
  "listing_url": "https://sg.jobstreet.com//job/95642329",
  "title": "Audit Associate / Audit Senior",
  "teaser": "Join AVENTROSS PAC as an Auditor and develop your technical and leadership skills.",
  "role_id": "audit-associate",
  "bullet_points": [
    "Competitive salary, performance bonuses and career progression",
    "Five-day work week with an office conveniently located near MRT",
    "Birthday and marriage leave, medical benefits and a supportive team environment"
  ],
  "classifications": [
    {
      "classification": {
        "id": "1200",
        "description": "Accounting"
      },
      "subclassification": {
        "id": "6144",
        "description": "Audit - External"
      }
    }
  ],
  "work_types": [
    "Full time"
  ],
  "work_arrangements": [
    "On-site"
  ],
  "salary_label": "$3,200 – $4,800 per month",
  "location": "City Hall, Central Region",
  "country_code": "SG",
  "locations": [
    {
      "label": "City Hall, Central Region",
      "country_code": "SG",
      "hierarchy": [
        "City Hall Central Region",
        "Central Region"
      ]
    }
  ],
  "company_name": "Aventross Pac",
  "employer_id": "3146143",
  "company_logo_url": "https://bx-branding-gateway.cloud.seek.com.au/f9c696c1-8094-4031-8531-fa7aeadbb487.1/jdpLogo",
  "advertiser_id": "63103763",
  "advertiser_name": "AVENTROSS PAC",
  "listing_date": "2026-11-02T09:24:48.000Z",
  "listing_date_display": "6d ago",
  "is_featured": false,
  "display_type": "standard",
  "ad_type": "ORGANIC",
  "raw_data": null,
  "from_url": "https://sg.jobstreet.com/audit-jobs"
}

Step-by-Step Usage Guide

Start by identifying the job searches relevant to your research or business needs. Visit JobStreet.com and perform searches using keywords, locations, and filters that match your target criteria. Note that different country domains (sg.jobstreet.com, my.jobstreet.com, ph.jobstreet.com) will return region-specific results.

Copy the URLs from your search results pages. If you want comprehensive data, include multiple page URLs from each search (page 1, 2, 3, etc.). Consider the trade-off between breadth and depth—searching many keywords shallowly versus fewer keywords more thoroughly.

Configure your input JSON with the collected URLs. Set max_items_per_url based on how many results you need per search. For quick market scans, 20-50 items may suffice. For comprehensive databases, increase this number or include more page URLs. Enable useApifyProxy if you're scraping large volumes or multiple country domains to avoid rate limiting.

Launch the scraper through the Apify console and monitor progress. Processing time varies based on the number of URLs and items per URL, but typically handles 100-200 job listings within 5-10 minutes. The scraper respects reasonable rate limits to avoid overloading JobStreet.com's servers.

Once completed, access your data through the dataset tab. Preview results to verify data quality and completeness. Export in JSON for programmatic analysis, CSV for spreadsheet tools, or directly integrate with your database systems using Apify's API.

For ongoing monitoring, schedule regular scraper runs (daily or weekly) to track new postings, removed listings, and changing market conditions. This time-series data reveals hiring velocity, seasonal patterns, and emerging skill demands before they become common knowledge.

Practical Applications and Strategic Value

The breadth of data from JobStreet.com search results enables numerous strategic applications across recruitment, market intelligence, and business development functions. Understanding these use cases helps maximize your return on investment in automated data collection.

Recruitment agencies can build real-time competitive intelligence by monitoring which companies are hiring for similar roles, what language they use in job titles and teasers, and how they structure their offerings. The isFeatured and branding fields reveal which competitors are investing heavily in visibility, potentially indicating urgent hiring needs or strong recruitment budgets.

Salary benchmarking becomes possible when analyzing the salaryLabel field across similar positions, locations, and seniority levels. While not all listings disclose compensation, those that do provide concrete market data points. Cross-referencing disclosed salaries with company size, industry classifications, and work arrangements reveals compensation patterns and helps establish competitive salary ranges.

Market researchers can track employment trends across Southeast Asian markets by running regular scrapes across multiple country domains. Comparing the volume of listings in different classifications over time indicates which industries are expanding or contracting. The workArrangements field provides insights into remote work adoption rates by industry and country, valuable for understanding regional labor market evolution.

Business development teams identify high-growth companies by monitoring hiring velocity. Companies posting multiple jobs across various functions are typically expanding, making them prime targets for B2B services, partnerships, or investment opportunities. The companyProfileStructuredDataId enables tracking all positions from specific employers.

Skills trend analysis emerges from examining job titles, classifications, and teasers at scale. Natural language processing on these fields reveals which technical skills, soft skills, and qualifications appear most frequently, helping educational institutions design relevant programs and professionals plan their skill development paths.

Geographic analysis using the locations field shows where job opportunities concentrate, informing relocation decisions, office location planning, and talent availability assessments. Comparing job volumes across Singapore's districts or between Malaysian cities provides granular insights into regional economic activity.

Best Practices for Sustainable and Effective Scraping

To maximize value while maintaining responsible data collection practices, implement these proven strategies in your scraping workflows.

Establish a reasonable collection schedule that balances data freshness with platform respect. For most use cases, daily scrapes of key searches or weekly comprehensive collections provide sufficient insight without excessive requests. JobStreet.com updates listings continuously, but daily changes are typically incremental rather than revolutionary.

Use targeted searches rather than attempting to scrape the entire platform. Focus on specific industries, locations, or role types relevant to your needs. This improves data quality by reducing noise and minimizes computational resources and scraping time.

Implement data deduplication based on the id field, as the same job may appear in multiple search results. Store historical data to track when listings appear and disappear, enabling time-to-fill analysis and detection of reposted positions that may indicate difficulty finding candidates.

Validate and clean your data systematically. Check that required fields are present, classify missing salary information appropriately, and standardize location names that may appear in various formats. Set up alerts for scraping failures or significant drops in result counts that might indicate platform changes.

Enrich scraped data with additional context. Combine JobStreet.com data with company financial information, employee reviews from platforms like Glassdoor, or competitive intelligence from other job boards to build comprehensive employer profiles.

Consider legal and ethical implications. Ensure your use of scraped data complies with local data protection regulations, particularly Singapore's PDPA and similar laws across Southeast Asian countries. Use the data for legitimate purposes like market research or recruitment operations rather than spamming job applicants.

Enable proxy rotation for large-scale operations. While small scrapes may work without proxies, significant data collection benefits from distributing requests across multiple IP addresses to avoid rate limiting and ensure consistent access.

Conclusion

The JobStreet.com Jobs Search Scraper unlocks Southeast Asia's largest employment platform as a structured data source, transforming scattered job listings into actionable market intelligence. Whether you're optimizing recruitment strategies, conducting regional market analysis, or identifying business opportunities, this tool provides the comprehensive data foundation needed for informed decision-making in one of the world's fastest-growing economic regions. Begin extracting insights from Southeast Asia's job market today and gain competitive advantage through data-driven intelligence.