We extract company profiles, job listings, equity bands, founder histories, and funding rounds from Angel.co (Wellfound). Delivered as clean JSON, CSV, or Parquet to S3 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 Company Profiles objects from angel.co. All fields typed and schema-versioned.
"company_id": "84921", "name": "Stripe", "website": "stripe.com", "employee_count": "1000-5000", "funding_stage": "Series I", "total_raised": 8700000000.0, "markets": "['Fintech', 'Payments', 'SaaS']"
| # | company_id | name | website | angel_url | location | employee_count |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Job Listings objects from angel.co. All fields typed and schema-versioned.
"job_id": "j-928174", "title": "Senior Backend Engineer", "role_type": "Full-time", "remote_policy": "Remote", "salary_min": 140000, "salary_max": 180000, "currency": "USD", "equity_min": 0.1, "equity_max": 0.25
| # | job_id | company_name | title | role_type | location | remote_policy |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Founder & Team Data objects from angel.co. All fields typed and schema-versioned.
"person_id": "p-10293", "name": "Patrick Collison", "role": "Co-Founder & CEO", "company": "Stripe", "twitter_url": "twitter.com/patrickc", "past_companies": "['Auctomatic']", "education": "['MIT']"
| # | person_id | name | role | company | linkedin_url | twitter_url |
|---|---|---|---|---|---|---|
| 1 | ||||||
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| 3 |
Complete list of extractable fields for Funding & Investors objects from angel.co. All fields typed and schema-versioned.
"round_type": "Series C", "amount_raised": 50000000, "currency": "USD", "date": "2024-02-15", "lead_investor": "Sequoia Capital", "participating_investors": "['Andreessen Horowitz', 'Founders Fund']"
| # | funding_id | company_name | round_type | amount_raised | currency | valuation |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Search & Discovery objects from angel.co. All fields typed and schema-versioned.
"keyword": "Artificial Intelligence", "position": 1, "company_name": "OpenAI", "signal_score": 9.8, "hiring_status": "Actively Hiring", "scraped_at": "2026-05-12T09:14:33Z"
| # | keyword | market_tag | position | company_name | signal_score | hiring_status |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Our Angel.co scraper targets the underlying GraphQL APIs and React states to extract company profiles, job listings, and equity bands - bypassing Cloudflare and session limits.
Capture company name, pitch, employee count, funding stage, markets, and total capital raised from thousands of startup profiles.
Extract highly accurate salary bands and equity percentages for engineering, product, and sales roles across global markets.
Map founder backgrounds, past exits, education, and social links to build detailed talent and investment graphs.
Track historical funding events, round types, capital raised, and participating investors for every company on the platform.
Extract the specific programming languages, frameworks, and infrastructure tools listed by engineering teams.
Monitor Wellfound Signal scores to identify trending startups and high-growth companies before they hit mainstream news.
Navigate infinite scroll and complex React pagination to ensure complete data extraction without missing records.
Bypass strict Cloudflare protection and rate limits using residential proxies and human-like request patterns.
Receive only new jobs, updated funding rounds, or changed salary bands to optimise your downstream storage.
Brief in. Clean data out.
Provide specific market tags, company sizes, or job roles. We configure the extraction schema to match your requirements.
We deploy Playwright spiders, residential proxies, and GraphQL interceptors to bypass Cloudflare on angel.co.
We test the pipeline for null-rate anomalies, salary outliers, and incomplete profiles before full production launch.
JSON, CSV, or Parquet files pushed to your S3 bucket or Snowflake environment on a daily or weekly schedule.
Angel.co employs aggressive bot mitigation and complex frontend rendering. We handle the infrastructure so you receive clean data.
Wellfound uses Cloudflare to block automated traffic. We utilise residential proxies and tailored Playwright contexts with authentic TLS fingerprints to solve challenges and maintain persistent sessions.
Instead of parsing complex React DOMs, our pipeline intercepts Wellfound internal GraphQL queries from the network tab, ensuring 100% accurate extraction of nested data like equity bands and tech stacks.
Certain data points on Angel.co require an active user session. We manage a pool of aged accounts with automated cookie rotation to access restricted job details and salary metrics safely.
When Wellfound updates their GraphQL schema, our monitors detect query payload changes immediately. We map new aliases to our normalised schema to prevent pipeline failure.
We hash job descriptions and salary bands to detect changes. Your warehouse receives a clean diff of new listings, closed roles, and modified compensation packages without redundant data.
Venture capital firms track hiring velocity and engineering headcount to identify breakout startups before their next funding round.
Startups monitor competitor job postings to understand product roadmaps and benchmark their own salary and equity offers.
Recruiters map founder networks and track employee movement between early-stage companies to source high-tier talent.
Analysts aggregate salary and equity data across thousands of listings to publish compensation reports for specific tech hubs.
Sales teams target newly funded companies that are actively expanding their engineering or marketing departments.
Funds correlate specific tech stack choices (e.g., Rust, AI frameworks) with funding success rates to validate market trends.
"Angel.co holds the most accurate equity and salary data for early-stage startups globally, but extracting it requires bypassing aggressive anti-scraping layers."
Most teams fail at scraping Wellfound because they rely on basic HTTP clients. We deploy full browser automation with residential proxies to bypass Cloudflare, execute React hydration, and extract clean GraphQL responses directly from the network tab. DataFlirt handles the infrastructure so your team can focus on analysis.
Everything supported by our angel.co scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
We bypass the complex React DOM entirely by using Playwright to intercept and parse the raw GraphQL responses that populate the Wellfound frontend.
Our proxy rotation logic uses high-quality US and EU residential IPs to bypass Cloudflare rate limits and IP reputation blocks seamlessly.
Airflow manages pipeline scheduling and dependency resolution, while Kubernetes scales Playwright browser instances horizontally to meet data volume demands.
Data delivered to where your team already works — no new tooling required.
About angel.co scraping, legality, and pipeline operations.
Ask us directly →Scraping public data from Angel.co is generally protected under rulings like hiQ v. LinkedIn. DataFlirt extracts only public company profiles, job listings, and founder histories. We do not extract private candidate data, internal recruiter messages, or violate GDPR. Clients must ensure their specific use cases comply with local regulations.
We use tailored Playwright browser contexts with residential proxies and specific TLS fingerprints to solve Cloudflare Turnstile challenges. Our request timing mimics human behaviour to prevent session invalidation.
Yes. We extract the exact minimum and maximum salary bands, currency, and equity percentages listed on every job posting.
We can run pipelines daily to capture new job postings and detect closed roles within 24 hours of the change occurring on Wellfound.
Yes. We map the complete list of programming languages, frameworks, and infrastructure tools associated with a company profile.
Our pipelines start at a defined set of market tags or specific company lists. We price based on data volume and extraction frequency. Contact us to scope your exact requirements.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a daily feed of new engineering jobs or a complete export of Series A startups - we build and operate the infrastructure. Tell us what you need.
