We extract job listings, equity ranges, founder profiles, tech stacks, and company funding signals from Wellfound. 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 wellfound.com. All fields typed and schema-versioned.
"job_id": "1492834", "title": "Senior Backend Engineer", "company_id": "83921", "location": "San Francisco, CA", "remote_policy": "Remote within US", "salary_min": 150000, "salary_max": 180000, "equity_min": 0.1, "equity_max": 0.5, "visa_sponsorship": false
| # | job_id | title | company_id | location | remote_policy | salary_min |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Company Profiles objects from wellfound.com. All fields typed and schema-versioned.
"company_id": "83921", "name": "FinScale", "industry": "Fintech", "size": "51-200", "funding_total": 24000000, "funding_stage": "Series A", "tech_stack": "['Python', 'React', 'PostgreSQL', 'AWS']", "employee_count": 84
| # | company_id | name | website | industry | size | location |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Salary & Equity objects from wellfound.com. All fields typed and schema-versioned.
"job_id": "1492834", "title": "Senior Backend Engineer", "currency": "USD", "base_salary_min": 150000, "base_salary_max": 180000, "equity_min": 0.1, "equity_max": 0.5, "updated_at": "2026-03-14T10:00:00Z"
| # | job_id | title | currency | base_salary_min | base_salary_max | equity_min |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Founders & Team objects from wellfound.com. All fields typed and schema-versioned.
"person_id": "92831", "name": "Sarah Jenkins", "current_role": "Co-Founder & CEO", "company_id": "83921", "linkedin_url": "linkedin.com/in/sarahjenkins", "twitter_url": "twitter.com/sarahj", "bio": "Former VP Product at Stripe.", "joined_date": "2022-01-15"
| # | person_id | name | current_role | company_id | linkedin_url | twitter_url |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Search Results objects from wellfound.com. All fields typed and schema-versioned.
"keyword": "machine learning", "location": "Remote", "position": 3, "company_name": "AI Dynamics", "job_title": "ML Engineer", "salary_range": "$140k - $190k", "remote_badge": true, "act_fast_badge": false, "scraped_at": "2026-03-14T10:15:00Z"
| # | keyword | location | position | company_name | job_title | salary_range |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Wellfound scraper navigates Cloudflare protections and dynamic React hydration to extract accurate compensation data, funding signals, and tech stacks at scale.
Company names, pitches, descriptions, funding stages, total capital raised, and employee count brackets mapped to unique company IDs.
Extract job titles, locations, remote policies, required experience levels, and visa sponsorship availability for every active role.
Capture base salary ranges, equity percentages, and currency types. Wellfound holds the most accurate early-stage compensation data.
Extract programming languages, frameworks, and infrastructure tools listed on company profiles and job descriptions.
Scrape founder bios, past experience, education, and social links to build comprehensive talent intelligence graphs.
Identify timezone overlap requirements, remote-first policies, and geographical hiring constraints.
Monitor 'Actively Hiring' badges, recent activity timestamps, and response rate indicators to gauge hiring urgency.
Extract industry tags like Fintech, SaaS, Web3, and AI to classify companies into specific market segments.
Run continuous pipelines to detect newly posted jobs, closed roles, and updated salary bands without downloading the entire catalogue.
Brief in. Clean data out.
Provide company URLs, search keywords, or industry tags. We design the extraction schema together.
We configure Scrapy crawlers, intercept GraphQL queries, and manage residential proxy rotation for wellfound.com.
Schema validation, null-rate checks, and salary outlier detection before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Wellfound protects its data with strict rate limits and dynamic front-end architectures. Here is how we maintain stable extraction.
Wellfound relies heavily on Cloudflare for bot mitigation. Our infrastructure uses residential proxies combined with TLS fingerprint spoofing and automated challenge solvers to maintain access without triggering blocks.
Instead of parsing complex React DOM structures, our Playwright sessions intercept the underlying GraphQL network requests. This provides cleaner, more structured data directly from Wellfound's backend.
Wellfound limits search results to a specific number of pages. We bypass this by programmatically slicing search queries by granular locations, salary brackets, and tech stacks to extract the full dataset.
We maintain a state index of all active jobs. Subsequent runs only push diffs, allowing you to accurately track exactly when a role is opened, updated, or closed.
Wellfound updates its GraphQL schema frequently. Our observability stack detects missing fields or type changes immediately, automatically pausing delivery and alerting our engineers to patch the selectors.
Recruiting agencies and internal talent teams map tech stacks and salary ranges to optimise their sourcing strategies.
VC firms monitor hiring velocity, key executive appointments, and tech stack choices as leading indicators of startup growth.
HR platforms aggregate Wellfound salary and equity data to build accurate compensation models for early-stage companies.
SaaS companies target startups based on their funding stage, employee count, and specific technologies listed in job descriptions.
Analysts track the rise of new programming languages and frameworks by analyzing occurrence rates in startup job postings.
Niche job boards syndicate remote and startup-specific roles to expand their catalogue and drive candidate traffic.
"Wellfound holds the most accurate equity and compensation signals for early-stage startups on the internet, but it is locked behind heavy rate limits and dynamic endpoints."
Extracting startup data requires navigating strict Cloudflare protections, complex React hydration states, and undocumented GraphQL queries. DataFlirt handles the proxy rotation, session management, and schema maintenance so your data science team can focus on identifying hiring signals and market trends.
Everything supported by our wellfound.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.
Playwright intercepts Wellfound's internal GraphQL queries, bypassing the need to parse complex React DOM structures and ensuring cleaner data extraction.
We maintain custom TLS fingerprints and residential proxy pools specifically tuned to navigate Wellfound's strict bot mitigation layers without detection.
Pipelines run on AWS ECS with Airflow managing dependency graphs and SLA alerting. State is maintained in Postgres for accurate change detection.
Data delivered to where your team already works — no new tooling required.
About wellfound.com scraping, legality, and pipeline operations.
Ask us directly →We extract all compensation data that is publicly visible on the platform. Wellfound is unique because it requires startups to post salary and equity ranges for most roles, making this data highly available and accurate.
Wellfound caps the number of visible results for broad searches. Our orchestration engine automatically slices broad queries into hundreds of granular micro-searches based on specific locations, salary bands, and tech stacks to ensure 100% coverage.
No. DataFlirt focuses exclusively on public company profiles, job listings, and founder information. We do not extract private candidate data, resumes, or bypass authentication walls intended to protect user privacy.
Pipelines can be configured to run daily or hourly. Our change detection system ensures that closed jobs are flagged and new postings are delivered within minutes of the pipeline completing its run.
Yes. We extract the funding stage and total capital raised from the company profile. By running continuous pipelines, we can log when a company updates its profile to reflect a new funding round.
Tech stacks and required skills are extracted as structured JSON arrays, making it simple to query for specific languages or frameworks in your data warehouse.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a complete export of startup profiles or a continuous feed of new engineering roles - we build and operate the infrastructure. Tell us your requirements.
