Levels.fyi Scraper

Extract verified tech compensation data from Levels.fyi — the trusted source for total compensation at 3,000+ tech companies including Google, Meta, Amazon, Apple, Microsoft and Netflix. Get base salary, stock grants (RSU), bonuses, levels and vesting schedules from self-reported, verified submissions.

Why use Levels.fyi Scraper?

Unlike Glassdoor or Salary.com, Levels.fyi shows total compensation — not just base salary. In tech, stock grants and bonuses can double or triple the base. A Google L5 engineer's base might be $245K, but total comp is $470K+ with RSUs and bonus. Levels.fyi is the only reliable public source for this breakdown.

This scraper uses structured markdown endpoints (.md) as primary data source — more stable than HTML parsing and immune to Levels.fyi's Next.js buildId rotation that breaks most competing scrapers.

What data can you extract?

Per company + role combination

Individual compensation submissions with: company name, job family, job title, company level (L3-L8, E3-E7, IC1-IC6), base salary, annual stock grant value, bonus, total compensation, years of experience, years at company, location, country and offer date.

Level breakdown (summary)

Median total compensation per level at each company — essential for understanding the pay bands and promotion economics.

How much does Levels.fyi Scraper cost?

Mode	Speed	Approximate cost
Per company×role	~10-15s per page	~$3 per 100 records
Multiple companies	+1 page per combo	~$5 per 100 records

Example output

{
  "company": "Google",
  "companySlug": "google",
  "jobFamily": "software-engineer",
  "jobTitle": "Backend Software Engineer",
  "level": "L5",
  "baseSalary": 245000,
  "stockGrant": 180000,
  "bonus": 45000,
  "totalCompensation": 470000,
  "yearsOfExperience": 8,
  "yearsAtCompany": 3,
  "location": "San Francisco Bay Area",
  "country": "United States",
  "offerDate": "2025-11-15",
  "sourceUrl": "https://www.levels.fyi/companies/google/salaries/software-engineer"
}

Input parameters

Quick start — FAANG software engineer salaries

{
  "companies": ["google", "meta", "amazon"],
  "jobFamilies": ["software-engineer"],
  "maxResults": 50
}

Full input reference

Parameter	Type	Default	Description
urls	array	[]	Direct Levels.fyi URLs — overrides company/role inputs
companies	array	[]	Company slugs: google, meta, amazon, apple, microsoft
jobFamilies	array	[]	Role slugs: software-engineer, product-manager, data-scientist
location	string	""	Filter by location: san-francisco-bay-area, new-york, seattle
maxResults	integer	100	Total record cap. 0 = unlimited
requestDelay	integer	2000	Delay between requests (ms)

Company slug format

Use the slug from any Levels.fyi company URL:

FAANG+: google · meta · amazon · apple · microsoft · netflix

Top tech: nvidia · salesforce · uber · lyft · airbnb · stripe · coinbase · databricks · snowflake · palantir · doordash · instacart · robinhood · discord · figma

Enterprise: oracle · sap · vmware · cisco · ibm · dell · hp · intel · qualcomm · adobe

Job family slugs

software-engineer · product-manager · data-scientist · product-designer · engineering-manager · devops-engineer · machine-learning-engineer · frontend-engineer · backend-engineer · mobile-engineer · security-engineer · site-reliability-engineer

Multi-company comparison

{
  "companies": ["google", "meta", "amazon", "apple", "microsoft"],
  "jobFamilies": ["software-engineer", "product-manager"],
  "maxResults": 200
}

Direct URL with markdown endpoint

{
  "urls": [
    "https://www.levels.fyi/companies/google/salaries/software-engineer.md",
    "https://www.levels.fyi/companies/meta/salaries/software-engineer.md"
  ]
}

How to scrape Levels.fyi compensation data

1. Click Try for free to open Levels.fyi Scraper in Apify Console
2. Enter company slugs (e.g. google, meta) and job families (e.g. software-engineer)
3. Optionally filter by location
4. Click Start and download results as JSON, CSV or Excel

Run programmatically via Apify API, schedule weekly runs for trend tracking, or integrate with Zapier, Make, Google Sheets and 100+ platforms.

Technical approach: why this scraper is more stable

Most Levels.fyi scrapers rely on HTML parsing or internal API calls that use Next.js buildId — a value that changes every time Levels.fyi deploys. When the buildId rotates, those scrapers break until manually updated.

This scraper takes a different approach:

1. Markdown endpoints first — Levels.fyi provides .md endpoints specifically for LLMs and crawlers. These return structured data that doesn't depend on buildId.
2. HTML + NEXT_DATA fallback — if markdown isn't available, the scraper extracts data from the Next.js hydration payload.
3. Playwright browser — real browser with Cloudflare bypass, no headless detection.

Use cases

Offer negotiation — Compare your offer against real compensation data at the same company, level and location. Know whether $350K TC at Google L4 is competitive or below market.

Compensation benchmarking — HR teams at tech companies benchmark their pay bands against FAANG and competitors. The level-by-level breakdown shows exactly where they stand.

Startup equity calibration — Startups competing for FAANG talent need to know the TC they're up against. Base + equity package must be competitive with public company RSU grants.

Recruiting intelligence — Staffing agencies use TC data to set realistic client expectations and craft winning offers for senior tech talent.

Market research — Analysts track compensation trends across tech companies, locations and experience levels for industry reports.

Career planning — Engineers evaluating L5→L6 promotion economics or Google→Meta switches need level-mapped TC comparisons.

Pay equity analysis — Researchers analyze TC distributions across locations, experience levels and roles for compensation fairness studies.

Output fields reference

Field	Description
company	Company name
companySlug	URL slug
jobFamily	Role category (software-engineer, PM, etc.)
jobTitle	Specific title (backend, frontend, ML, etc.)
level	Company level (L3-L8, E3-E7, IC1-IC6)
baseSalary	Annual base salary (USD)
stockGrant	Annual RSU/equity value (USD)
bonus	Annual bonus (USD)
totalCompensation	Total annual comp = base + stock + bonus
yearsOfExperience	Total career experience
yearsAtCompany	Tenure at current company
location	City/metro area
country	Country
offerDate	When the comp data was submitted
medianTC	Median total comp (summary mode)
levelBreakdown	Per-level median TC breakdown

Integrations

Levels.fyi Scraper works with the full Apify ecosystem: API access from Python/Node.js/PHP, webhooks, Google Sheets export, Zapier/Make automation, and Slack/email notifications.

Limitations

• Tech companies only — Levels.fyi focuses on technology sector
• Self-reported data (verified badge system provides quality control)
• Primarily US compensation data, some international submissions available
• Stock grant values are annualized estimates — actual vesting varies
• Cloudflare protection requires Playwright browser — slightly higher compute cost
• Some company×role combinations may have limited submissions