We extract freelancer profiles, job postings, agency statistics, and skill ontologies from Upwork. 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 Freelancer Profiles objects from upwork.com. All fields typed and schema-versioned.
"profile_id": "freelancer_98421", "name": "Jane D.", "title": "Senior React Developer", "hourly_rate": 85.0, "total_earned": "100k+", "job_success_score": 98, "location": "London, UK"
| # | profile_id | name | title | hourly_rate | location | total_earned |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Job Postings objects from upwork.com. All fields typed and schema-versioned.
"job_id": "job_4928174", "title": "Build a Next.js Dashboard", "type": "Hourly", "hourly_range_min": 40.0, "hourly_range_max": 75.0, "client_spend": "50k+", "client_rating": 4.9, "posted_time": "2026-05-12T10:15:00Z"
| # | job_id | title | category | type | budget | hourly_range_min |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Agency Data objects from upwork.com. All fields typed and schema-versioned.
"agency_id": "agency_112", "agency_name": "DevStudio Tech", "total_earned": "1M+", "members_count": 24, "top_rated_status": "Top Rated Plus", "active_jobs": 14, "total_hours": 45000
| # | agency_id | agency_name | tagline | total_earned | hourly_rate | location |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Project Catalogue objects from upwork.com. All fields typed and schema-versioned.
"project_id": "pc_8832", "title": "I will design a modern SaaS landing page", "price_tier_1": 500.0, "price_tier_2": 800.0, "delivery_time": 5, "rating": 5.0, "orders_in_queue": 3
| # | project_id | title | freelancer_name | price_tier_1 | price_tier_2 | delivery_time |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Client History objects from upwork.com. All fields typed and schema-versioned.
"client_id": "client_994", "total_spent": 142000.0, "average_hourly_rate": 55.5, "total_hires": 42, "active_hires": 3, "rating": 4.8, "verification_status": "Payment verified"
| # | client_id | total_spent | average_hourly_rate | total_hires | active_hires | location |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Our Upwork scraper handles every layer of the platform, talent search, job feeds, agency statistics, and project catalogues, with JavaScript rendering and anti-bot circumvention built in.
Name, title, hourly rate, total earned, Job Success Score, and skill tags. Scraped at profile level with full history.
Capture budget, hourly range, required skills, and client spend history. Timestamped per crawl.
Extract agency name, member count, total hours billed, and Top Rated status across all active agencies.
Track demand for specific skills and certifications across millions of job postings and profiles.
Monitor average hourly rates by geography, skill, and experience level for market benchmarking.
Client rating, total spent, average hourly rate paid, and hire count for every job posting.
Track pre-packaged projects, pricing tiers, delivery times, and order queue depths.
Filter and scrape talent pools by specific countries, timezones, and language proficiencies.
Run one-off bulk exports or configure continuous pipelines at hourly or daily cadences with change detection.
Brief in. Clean data out.
Provide skill keywords, category URLs, or agency IDs. We design the extraction schema together.
We configure Scrapy and Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for upwork.com.
Schema validation, null-rate checks, and sample profiles before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Upwork deploys strict scraping detection via Cloudflare. Here is how we stay resilient, and why teams choose managed infrastructure over DIY.
Upwork bot detection operates on TLS fingerprints and IP reputation. Our crawlers use residential ISP proxies with realistic browser fingerprints, randomised request timing, and full cookie session management.
Upwork search results and profiles are heavily JavaScript-rendered single page applications. We run full Playwright browser sessions with JavaScript execution and lazy-load triggering.
Upwork changes its DOM structure frequently. Our selector strategy uses multiple fallback chains per field, CSS selectors, XPath, and API interception, so a layout change does not break your data pipeline.
For large talent pools, we maintain a hash index of last-seen values per field. Subsequent runs only push diffs, reducing compute cost and downstream processing load.
Every run emits structured logs to our observability stack. We alert on null-rate spikes, schema drift, and coverage drops, and respond before you notice.
Recruitment teams build proprietary talent pools by scraping top-rated profiles for specific technical skills.
HR and finance teams track hourly rate trends across geographies to optimise global hiring budgets.
Sales teams identify companies spending heavily on freelance platforms to pitch enterprise software or agency services.
Agencies monitor competitor pricing, client feedback, and active job volume to adjust their own positioning.
Researchers and investment firms track platform growth, category demand, and overall transaction volume indicators.
EdTech companies analyse required skills in job postings to develop relevant curriculum and training programs.
"Upwork holds the world's most precise dataset on freelance market rates and skill demand, but extracting it requires navigating aggressive bot mitigation."
Most teams underestimate the investment required: reliable Upwork scraping requires residential proxies, full JavaScript rendering, CAPTCHA handling, 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 upwork.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. Rotation happens per-request with sticky sessions where required. IP score monitoring prevents blacklisted pool contamination.
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 upwork.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from Upwork is generally permissible under applicable law, reinforced by the hiQ v. LinkedIn ruling. DataFlirt targets only public, non-authenticated profile, job, and agency data. We do not extract personal contact details or circumvent authentication walls. Clients should review Upwork Terms of Service and consult legal counsel for specific use cases.
We use residential ISP proxies, full Playwright browser sessions with realistic fingerprints, and request timing modelled on human behaviour. We monitor for 403 blocks in real time and trigger pool rotation automatically.
Real-time streaming pipelines achieve sub-60-minute latency for new job postings. Full category talent refreshes at weekly cadence complete within a 12-24 hour window depending on scale.
Yes. We can target exact skill tags, Job Success Scores, location requirements, and hourly rate bands to narrow the extraction scope.
Our smallest packages start at a defined keyword set or category list with weekly delivery. For larger datasets, we price based on volume and delivery frequency. Contact us with your use case for a scoped quote.
Absolutely. We provide a sample run of up to 500 profiles or job postings as part of the pre-engagement scoping process, so you can validate schema fit and data quality before signing any contract.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off talent pool dump or a continuous job monitoring feed across 50 categories, we scope, build, and operate the pipeline. Tell us what you need.
