We extract job listings, salary estimates, company reviews, and skill requirements from Jobstreet. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your cadence.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Job Postings objects from jobstreet.com. All fields typed and schema-versioned.
"job_id": "JS-984729", "title": "Senior Software Engineer", "company_name": "TechCorp Asia", "location": "Kuala Lumpur", "salary_min": 12000, "salary_max": 18000, "work_type": "Full Time", "date_posted": "2023-10-24T08:30:00Z"
| # | job_id | title | company_name | location | classification | sub_classification |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Company Profiles objects from jobstreet.com. All fields typed and schema-versioned.
"company_id": "C-44921", "name": "TechCorp Asia", "industry": "Information Technology", "size": "501-1000", "rating": 4.2, "review_count": 342, "jobs_count": 15
| # | company_id | name | industry | website | size | headquarters |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Salary Data objects from jobstreet.com. All fields typed and schema-versioned.
"job_id": "JS-984729", "currency": "MYR", "salary_min": 12000, "salary_max": 18000, "salary_type": "Monthly", "salary_visible": true, "market_estimate": 15000
| # | job_id | title | company_name | location | currency | salary_min |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Skill Requirements objects from jobstreet.com. All fields typed and schema-versioned.
"job_id": "JS-984729", "required_skills": "['Python', 'AWS', 'PostgreSQL']", "years_experience": 5, "education_level": "Bachelor's Degree", "languages": "['English', 'Malay']", "certifications": "['AWS Certified Solutions Architect']"
| # | job_id | title | classification | required_skills | preferred_skills | years_experience |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Search Results objects from jobstreet.com. All fields typed and schema-versioned.
"keyword": "Data Engineer", "location": "Singapore", "position": 3, "job_id": "JS-11234", "is_promoted": false, "posted_time": "2 hours ago", "salary_snippet": "SGD 6,000 - SGD 9,000"
| # | keyword | location | page_number | position | job_id | title |
|---|---|---|---|---|---|---|
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Our Jobstreet scraper handles every layer of the platform: job listings, company profiles, salary bands, and skill requirements - with JavaScript rendering and anti-bot circumvention built in.
Title, description, location, work type, and classification hierarchy extracted at scale.
Capture stated salary ranges, currency, and pay periods across all job listings.
Extract industry classification, company size, benefits, and active job counts for employer analysis.
Isolate required experience levels, educational qualifications, and specific technical skills.
Track sponsored vs organic job placements across specific search keywords and locations.
jobstreet.com.my, jobstreet.com.sg, jobstreet.co.id, and jobstreet.com.ph supported natively.
Monitor posting velocity, duration active, and expired listings over time.
Filter and extract roles tagged for remote, hybrid, or on-site work models.
Run daily pipelines that output only new, updated, or closed jobs to minimise storage bloat.
Brief in. Clean data out.
Provide target locations, job classifications, or company lists. We map the extraction schema.
We configure Scrapy crawlers, proxy rotation, and session management for jobstreet.com.
Schema validation, null-rate checks, and data normalisation before full production launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage.
Jobstreet uses commercial bot protection and dynamic front-end frameworks. Here is how we stay resilient.
Jobstreet uses commercial bot protection. Our crawlers use residential ISP proxies with realistic TLS fingerprints and HTTP headers.
Many Jobstreet elements load asynchronously via GraphQL APIs. We intercept these network requests directly or render via Playwright.
Jobstreet updates its front-end framework frequently. We use multi-layer fallback chains and API payload extraction to prevent breakages.
We hash job IDs and content states. Subsequent runs only emit new jobs, closed jobs, or modified listings.
Every run emits structured logs. We alert on null-rate spikes in salary fields or coverage drops across classifications.
Economists and researchers track hiring trends, skill demand, and salary inflation across Southeast Asia.
Enterprises monitor competitor hiring velocity, open roles, and department expansion signals.
HR teams aggregate salary bands by role and location to optimise compensation packages.
B2B sales teams identify companies expanding specific departments to pitch relevant software or services.
Niche job boards and aggregators backfill their platforms with targeted Jobstreet listings.
EdTech companies analyse required skills in job postings to design relevant training courses and curricula.
"Jobstreet holds the most accurate pulse on Southeast Asia's labour market - but extracting that data requires navigating complex bot protection and dynamic front-ends."
Most teams underestimate the investment required: reliable Jobstreet scraping demands residential proxies, GraphQL API interception, daily selector maintenance, and anomaly monitoring. DataFlirt absorbs that complexity so your engineers can focus on the analysis, not the infrastructure.
Everything supported by our jobstreet.com scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Scrapy handles crawl orchestration, deduplication, and retry logic. Playwright handles JavaScript rendering, cookie sessions, and interaction flows.
We maintain pools of residential ISP proxies across SG/MY/ID/PH regions. Rotation happens per-request with sticky sessions where required.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling, dependency management, and SLA alerting. All state stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About jobstreet.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available job postings is generally permissible under applicable laws. DataFlirt targets only public, non-authenticated job and company data. We do not extract personal candidate information or circumvent authentication walls.
We use residential ISP proxies, realistic browser fingerprints, and request timing modelled on human behaviour. We monitor for 403 blocks in real time and trigger pool rotation automatically.
We support jobstreet.com.my, jobstreet.com.sg, jobstreet.co.id, and jobstreet.com.ph, delivering data in a unified, normalised schema.
Daily pipelines capture new job postings within 24 hours of publication. Real-time monitoring can be configured for specific high-priority search keywords.
Yes. Our change detection system checks the status of previously scraped job IDs. If a listing is removed or marked inactive, we emit an updated status record.
We extract salary ranges if they are visible in the page DOM or API payload. We cannot extract salaries that are entirely withheld by the employer on the backend.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a daily feed of tech jobs in Singapore or a historical archive of salary trends across Malaysia - we scope, build, and operate the pipeline. Tell us what you need.
