We extract freelancer portfolios, job postings, hourly rates, SafePay transaction history, and employer profiles from Guru. 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 guru.com. All fields typed and schema-versioned.
"id": "F982341", "name": "Jane Doe", "hourly_rate": 45.0, "all_time_earnings": 125400.0, "location": "London, UK", "skills": "['Python', 'Data Engineering', 'AWS']"
| # | id | name | username | tagline | hourly_rate | all_time_earnings |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Job Postings objects from guru.com. All fields typed and schema-versioned.
"job_id": "J491023", "title": "Build a PostgreSQL Data Warehouse", "budget_type": "Fixed", "budget_max": 5000.0, "quotes_received": 14, "posted_date": "2026-05-10T14:30:00Z"
| # | job_id | title | category | sub_category | description | budget_type |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Employer Profiles objects from guru.com. All fields typed and schema-versioned.
"employer_id": "E119284", "total_spent": 450000.0, "jobs_posted": 42, "safepay_transactions": 38, "location": "New York, USA", "rating": 4.9
| # | employer_id | name | location | joined_date | jobs_posted | total_spent |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Freelancer Portfolios objects from guru.com. All fields typed and schema-versioned.
"item_id": "P884712", "title": "E-commerce React Application", "skills_used": "['React', 'Node.js', 'Redux']", "image_url": "https://guru.com/portfolio/img1.jpg", "uploaded_date": "2025-11-20", "view_count": 1204
| # | item_id | freelancer_id | title | description | category | skills_used |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Reviews & Feedback objects from guru.com. All fields typed and schema-versioned.
"review_id": "R993821", "rating": 5.0, "review_text": "Excellent communication and delivered ahead of schedule.", "date": "2026-02-14", "amount_earned": 1200.0, "feedback_type": "Employer to Freelancer"
| # | review_id | freelancer_id | employer_id | job_id | rating | review_text |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Our Guru scraper captures the entire freelance ecosystem: talent profiles, historical earnings, employer job postings, and quote volumes, with full pagination handling and anti-bot circumvention built in.
Extract bio text, hourly rates, all-time earnings, skills, and member status across the entire talent pool.
Capture budgets, categories, descriptions, and real-time quote counts for active projects.
Track total spent, SafePay history, invoice counts, and employer ratings to qualify buyers.
Scrape portfolio item titles, descriptions, tagged skills, and image URLs to assess talent quality.
Extract ratings, detailed review text, and job context for historical transactions.
Extract structured skills and categories to map talent liquidity across specific technical domains.
Capture SafePay and invoice statistics to understand true transaction volumes.
Map geographic distribution of talent and employers to identify regional pricing differences.
Track new job postings or rate changes over time with continuous pipeline execution.
Brief in. Clean data out.
Provide categories, keywords, or profile URLs. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, and session management for guru.com.
Schema validation, null-rate checks, and sample profiles before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Extracting data from freelance marketplaces requires navigating rate limits, dynamic search results, and complex pagination structures. Here is how our infrastructure maintains stability.
Job boards monitor request velocity and browser fingerprints. Our crawlers use residential ISP proxies with realistic browser profiles, randomised request timing, and full cookie session management trained on real user behaviour patterns.
Guru search results use complex state and dynamic loading. We implement custom pagination logic to ensure complete extraction across deep search categories without missing records.
Marketplace layouts change frequently. Our selector strategy uses multiple fallback chains per field, including CSS selectors, XPath, and text-pattern matching, so a DOM change does not break your data pipeline overnight.
For large talent catalogues, 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, responding before you notice.
Track freelance rates across skills and geographies to benchmark compensation trends.
Other platforms monitor talent liquidity, project volumes, and category growth to inform strategy.
B2B service providers target high-spend employers based on historical transaction data.
Recruitment agencies aggregate niche skills and portfolio data to build proprietary talent pools.
Agencies benchmark hourly rates and fixed budgets for specific project types to optimise bids.
Economists study gig economy trends, earnings distribution, and remote work adoption.
"Freelance marketplaces hold the most accurate pricing data for global talent, but extracting it at scale requires dedicated infrastructure."
Most teams underestimate the investment required to maintain a marketplace scraper. Guru's search pagination, rate limits, and nested profile structures require residential proxies, daily selector maintenance, and anomaly monitoring. DataFlirt absorbs that complexity so your engineers can focus on the analysis, rather than the extraction infrastructure.
Everything supported by our guru.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 multiple regions. 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 is stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About guru.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from Guru is generally permissible under applicable law, reinforced by the hiQ v. LinkedIn ruling. DataFlirt targets only public, non-authenticated profile and job data. We do not extract personal data, circumvent authentication walls, or violate GDPR. Clients should review 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 rate limit spikes in real time and trigger pool rotation automatically.
Yes, we extract all public transaction data available on employer and freelancer profiles, including total spent, all-time earnings, and SafePay transaction counts.
Daily refreshes complete within a 6-12 hour window depending on catalogue size. Historical snapshots are available from the day your pipeline is commissioned.
Yes, we monitor active job listings to capture budget ranges, fixed prices, and the number of quotes received over time.
Yes, including project titles, descriptions, tagged skills, and image URLs to provide a complete view of talent capabilities.
Our smallest packages start at a defined search set, typically 10,000 to 50,000 profiles, with weekly delivery. For larger catalogues or custom schema requirements, we price based on volume and delivery frequency.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off talent pool export or a continuous feed of new job postings, we scope, build, and operate the pipeline. Tell us what you need.
