We extract job listings, salary bands, company details, and location data from Jobsora. 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 Listings objects from jobsora.com. All fields typed and schema-versioned.
"job_id": "js_98127364", "title": "Senior Data Engineer", "company_name": "TechCorp Solutions", "location": "London, UK", "employment_type": "Full-time", "posted_date": "2026-10-14", "salary_min": 75000, "salary_max": 95000, "currency": "GBP", "remote_flag": true
| # | job_id | title | company_name | location | employment_type | posted_date |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Company Data objects from jobsora.com. All fields typed and schema-versioned.
"company_id": "comp_84712", "company_name": "TechCorp Solutions", "industry": "Information Technology", "location": "London, UK", "job_count": 42, "rating": 4.2, "website": "techcorpsolutions.co.uk"
| # | company_id | company_name | industry | location | job_count | rating |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Salary Insights objects from jobsora.com. All fields typed and schema-versioned.
"job_id": "js_98127364", "title": "Senior Data Engineer", "salary_min": 75000, "salary_max": 95000, "currency": "GBP", "pay_period": "ANNUAL", "estimated_flag": false
| # | job_id | title | company_name | salary_min | salary_max | currency |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Location Data objects from jobsora.com. All fields typed and schema-versioned.
"job_id": "js_98127364", "city": "London", "state": "Greater London", "country": "UK", "remote_flag": true, "hybrid_flag": false, "exact_location": "Canary Wharf"
| # | job_id | city | state | country | postal_code | remote_flag |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Search Results objects from jobsora.com. All fields typed and schema-versioned.
"keyword": "data engineer", "location_query": "London", "position": 3, "job_id": "js_98127364", "title": "Senior Data Engineer", "company_name": "TechCorp Solutions", "sponsored_flag": false
| # | keyword | location_query | position | job_id | title | company_name |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Jobsora scraper navigates geo-restrictions, paginates through thousands of search results, and normalises fragmented job data into clean, queryable records.
Title, description, company, location, employment type, and application URLs extracted from every job post.
Extract minimum and maximum salary ranges, currencies, and pay periods. Normalise inconsistent formats into standard numerical fields.
Scrape jobs specific to cities, regions, or countries using localised residential proxies to bypass geo-blocks.
Jobsora aggregates from multiple sources. We apply hash-based deduplication to ensure you only receive unique job postings.
Identify flexible working arrangements by parsing metadata and job descriptions for remote or hybrid indicators.
Extract aggregated company metrics, industry tags, and active job counts directly from employer pages.
Track new openings and closed positions. Subsequent runs only push diffs to reduce compute cost and storage bloat.
Extract data from Jobsora's UK, US, EU, and APAC domains using a unified extraction schema.
Run one-off bulk exports or configure continuous pipelines at hourly or daily cadences.
Brief in. Clean data out.
Provide keywords, locations, or company names. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for jobsora.com.
Schema validation, null-rate checks, deduplication testing, and sample data review before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Job aggregators present unique scraping challenges: massive scale, duplicate listings, and aggressive geo-fencing. Here is how we solve them.
Jobsora serves different content based on IP location. We route requests through residential ISP proxies matching your target region, ensuring you see the exact job market data a local user would see.
Because Jobsora aggregates listings from thousands of smaller boards, duplicate postings are common. We generate a unique hash based on title, company, and location to filter out redundant records before delivery.
Application links and salary details are often obfuscated or loaded dynamically. We run full Playwright browser sessions to execute JavaScript, revealing hidden contact details and outbound URLs.
Job board layouts change frequently to deter scraping. Our selector strategy uses multiple fallback chains per field, so a minor DOM update does not break your data pipeline.
Every run emits structured logs to our observability stack. We alert on null-rate spikes, volume drops, and schema drift, responding before you notice missing data.
Economists and research firms track hiring volume, remote work trends, and sector growth by analysing historical job posting data.
HR teams monitor competitor job postings to understand strategic shifts, new department expansions, and hiring velocity.
Niche job boards backfill their inventory by programmatically extracting relevant roles from Jobsora's massive catalogue.
Recruitment agencies extract salary ranges across thousands of similar roles to build accurate compensation models for clients.
Hedge funds and institutional investors use real-time job posting volume as a leading indicator of corporate health and economic expansion.
Sales teams track companies hiring for specific roles (e.g., VP of Engineering) as intent signals for purchasing enterprise software.
"Jobsora aggregates millions of global job postings, creating a massive but fragmented dataset that requires strict deduplication and normalisation to be useful."
Extracting global job data requires circumventing regional geo-blocks, standardising inconsistent salary formats, and maintaining state across millions of listings. DataFlirt handles the proxy routing, deduplication, and schema normalisation so you get clean, queryable labour data without running the infrastructure.
Everything supported by our jobsora.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. Combined via scrapy-playwright middleware.
We maintain pools of residential ISP proxies across global regions. Rotation happens per-request with sticky sessions where required. IP score monitoring prevents blacklisted pool contamination.
Pipelines run on AWS Lambda (burst) and ECS (sustained). 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 jobsora.com 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 circumvent authentication walls. Clients should review Jobsora's ToS and consult legal counsel for specific use cases.
Jobsora is an aggregator, meaning the same job often appears multiple times. We use a deterministic hashing algorithm based on job title, company name, and location to filter out duplicates before delivery.
Yes. We use localised residential proxies to access region-specific Jobsora domains, ensuring we extract the exact postings available to local job seekers.
We can configure pipelines to run hourly, daily, or weekly. For time-sensitive recruitment use cases, delta syncs provide sub-60-minute latency for new job postings matching your criteria.
Yes. Job descriptions often contain unstructured salary text. We parse this into standard numerical fields (salary_min, salary_max), identify the currency, and specify the pay period (hourly, monthly, annual).
Absolutely. We provide a sample run of up to 1,000 job postings matching your target keywords and locations as part of the pre-engagement scoping process.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off export of tech roles in London or a continuous feed of global hiring data — we scope, build, and operate the pipeline. Tell us what you need.
