We extract job listings, salary bands, company profiles, and location metadata from CareerOne. 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 careerone.com.au. All fields typed and schema-versioned.
"job_id": "CO-982341", "title": "Senior Data Engineer", "company_name": "TechCorp Australia", "location": "Sydney, NSW", "salary_text": "$130,000 - $160,000", "job_type": "Full Time", "is_remote": true, "posted_date": "2026-05-10T08:30:00Z"
| # | job_id | title | company_name | location | salary_text | job_type |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Company Profiles objects from careerone.com.au. All fields typed and schema-versioned.
"company_id": "COMP-4451", "name": "TechCorp Australia", "industry": "Information Technology", "company_size": "500-1000", "active_job_count": 24, "headquarters": "Sydney", "website_url": "https://techcorp.com.au"
| # | company_id | name | industry | company_size | website_url | logo_url |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Salary Data objects from careerone.com.au. All fields typed and schema-versioned.
"job_id": "CO-982341", "job_title": "Senior Data Engineer", "raw_salary_string": "$130k - $160k + Super", "parsed_min": 130000, "parsed_max": 160000, "currency": "AUD", "pay_period": "ANNUAL", "includes_superannuation": true
| # | job_id | job_title | location | raw_salary_string | parsed_min | parsed_max |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Search Results objects from careerone.com.au. All fields typed and schema-versioned.
"search_keyword": "data engineer", "search_location": "Melbourne", "rank_position": 1, "job_id": "CO-982341", "title": "Senior Data Engineer", "company": "TechCorp Australia", "is_promoted": false, "scraped_at": "2026-05-12T10:15:00Z"
| # | search_keyword | search_location | rank_position | job_id | title | company |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Recruiter Info objects from careerone.com.au. All fields typed and schema-versioned.
"recruiter_id": "REC-7721", "agency_name": "DataTalent Partners", "contact_name": "Sarah Jenkins", "active_listings": 45, "location": "Brisbane, QLD", "specialisation": "Technology Data", "agency_website": "https://datatalent.com.au"
| # | recruiter_id | agency_name | contact_name | active_listings | location | agency_website |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our CareerOne scraper handles the complete job marketplace: active listings, company profiles, and salary bands with built-in anti-bot circumvention and JavaScript rendering.
Extract complete HTML or plain text job descriptions, preserving bullet points, formatting, and required skill lists.
Convert raw salary text into structured minimum, maximum, and currency fields with superannuation flags.
Capture company size, industry categorisation, website links, and active job counts directly from employer profiles.
Map raw location strings to standard Australian suburbs, states, and postcodes for accurate geographic analysis.
Distinguish between organic search results and sponsored placements to analyse employer advertising spend.
Identify whether a role is posted directly by the employer or through a third-party recruitment agency.
Extract work models including fully remote, hybrid, and on-site requirements from job metadata.
Only scrape new or updated job postings, reducing data bloat and focusing purely on market changes.
Run continuous pipelines at hourly or daily cadences to capture jobs before they expire or get filled.
Brief in. Clean data out.
Provide keywords, locations, or company URLs. We design the extraction schema together.
We configure Scrapy and Playwright crawlers, proxy rotation, and session management for careerone.com.au.
Schema validation, null-rate checks, and sample extraction before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Job boards deploy strict scraping countermeasures to protect their core asset. Here is how we maintain resilient access.
Job boards monitor request velocity and IP reputation. Our crawlers use residential ISP proxies with realistic browser fingerprints and randomised request timing to bypass perimeter defences.
CareerOne search results and job details rely on client-side rendering. We run full Playwright browser sessions to trigger lazy-loads and capture data that headless HTTP clients miss entirely.
DOM structures change without notice. Our selector strategy uses multiple fallback chains per field, including CSS selectors, XPath, and text-pattern matching to ensure stable extraction.
For large market scans, we maintain a hash index of last-seen jobs. Subsequent runs only push diffs, reducing compute cost and downstream processing load.
Every run emits structured logs. We alert on null-rate spikes, schema drift, and coverage drops, responding before you notice any data gaps.
Economists and analysts track hiring trends, skill demand, and geographic shifts in the Australian workforce.
Enterprises monitor competitor hiring velocity and role prioritisation to infer strategic direction.
HR teams aggregate compensation bands across specific roles and locations to remain competitive.
Sales teams identify growing companies based on aggressive hiring patterns and specific technology requirements.
Agencies find direct employer listings to identify new client acquisition opportunities.
Hedge funds use job posting volume as a leading macroeconomic indicator for sector growth.
"CareerOne represents a critical pulse on the Australian labour market, but extracting structured intelligence requires dedicated infrastructure."
Most data teams underestimate the complexity of job board extraction. Maintaining reliable access to CareerOne requires residential proxies, full browser rendering, and constant selector maintenance. DataFlirt absorbs this operational overhead so your engineering team can focus on downstream analytics rather than pipeline repairs.
Everything supported by our careerone.com.au 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 and deduplication. Playwright handles JavaScript rendering and interaction flows. Combined via scrapy-playwright middleware.
We maintain pools of residential ISP proxies across AU regions. Rotation happens per-request with sticky sessions where required.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling and dependency management. All state stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About careerone.com.au scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available job postings is generally permissible under applicable law. DataFlirt targets only public, non-authenticated job and company data. We do not extract personal candidate data or breach authentication walls.
We use residential ISP proxies, full Playwright browser sessions with realistic fingerprints, and request timing modelled on human behaviour to maintain access.
Pipelines can be configured to run daily or hourly. Real-time streaming is available for targeted keyword monitors to capture roles immediately upon posting.
Yes. We use custom regex pipelines to extract minimum and maximum numerical values from unstructured text strings, normalising them to annualised AUD figures.
Our change detection system logs when a previously seen job ID is no longer present in search results or returns a 404, allowing you to mark the role as closed.
Absolutely. We provide a sample run of up to 500 job listings as part of the scoping process so you can validate schema fit and data quality.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off export of the technology sector or a continuous feed of all Australian job listings, we build and operate the pipeline. Tell us what you need.
