Levels.fyi Salary Scraper

Scrape salary and compensation data from Levels.fyi. Extract total compensation, base salary, stock grants, bonuses, and more by company and job title.

What does Levels.fyi Salary Scraper do?

Levels.fyi is the leading salary comparison platform for tech workers. This actor extracts structured compensation data including base salary, stock grants, bonuses, and total compensation broken down by company, job title, level, and location.

Whether you are benchmarking salaries for hiring, negotiating your next offer, or conducting compensation research across the tech industry, this actor gives you programmatic access to the salary data that thousands of tech workers rely on every day.

The actor uses efficient HTTP-based scraping (no browser needed) by extracting structured data directly from the page source, making it fast and cost-effective.

Use Cases

• Recruiters and HR teams -- Benchmark compensation packages against market rates for specific roles and levels
• Job seekers -- Research salary ranges before negotiating offers at target companies
• Data analysts -- Build compensation datasets for market analysis and salary trend reports
• Startup founders -- Set competitive compensation bands based on real market data

Features

• Scrape salary data by company, job title, and level
• Extract total compensation, base salary, stock grants, and bonuses
• Location and years of experience data included
• Build URLs automatically from company names and job titles
• Proxy support with automatic rotation
• Handles pagination and large datasets automatically
• Exports to JSON, CSV, Excel, or connect via API

How much will it cost?

Results	Estimated Cost
100	~$0.50
1,000	~$3.00
10,000	~$25.00

Cost Component	Per 1,000 Results
Platform compute	~$0.50
Proxy (residential)	~$2.50
Total	~$3.00

How to use

1. Go to the Levels.fyi Salary Scraper page on Apify Store
2. Click "Start" or "Try for free"
3. Enter company names or Levels.fyi URLs
4. Set the maximum number of items
5. Click "Start" and wait for the results

Input parameters

Parameter	Type	Description	Default
startUrls	array	Levels.fyi URLs to scrape	-
companies	array	Company names (e.g. google, meta)	-
jobTitles	array	Job titles (e.g. software-engineer)	-
maxItems	number	Max results to return	100
maxConcurrency	number	Parallel page limit	5
proxyConfig	object	Proxy settings	Residential

Output

The actor produces a dataset with the following fields:

{
    "company": "Google",
    "title": "Software Engineer",
    "level": "L5",
    "totalCompensation": 350000,
    "baseSalary": 185000,
    "stockGrant": 120000,
    "bonus": 45000,
    "location": "Mountain View, CA",
    "yearsOfExperience": 6,
    "yearsAtCompany": 3,
    "gender": "Male",
    "timestamp": "2024-06-15T00:00:00.000Z",
    "url": "https://www.levels.fyi/companies/google/salaries/software-engineer",
    "scrapedAt": "2024-07-01T12:00:00.000Z"
}

Field	Type	Description
company	string	Company name
title	string	Job title
level	string	Job level (e.g. L5, E5, Senior)
totalCompensation	number	Total yearly compensation in USD
baseSalary	number	Base salary in USD
stockGrant	number	Yearly stock/equity grant in USD
bonus	number	Yearly bonus in USD
location	string	Work location
yearsOfExperience	number	Total years of experience
yearsAtCompany	number	Years at current company
gender	string	Self-reported gender
timestamp	string	When the salary was reported
url	string	Source page URL
scrapedAt	string	ISO 8601 scrape timestamp

Integrations

Connect Levels.fyi Salary Scraper with other tools:

• Apify API -- REST API for programmatic access
• Webhooks -- get notified when a run finishes
• Zapier / Make -- connect to 5,000+ apps
• Google Sheets -- export directly to spreadsheets

API Example (Node.js)

import { ApifyClient } from 'apify-client';
const client = new ApifyClient({ token: 'YOUR_TOKEN' });
const run = await client.actor('YOUR_USERNAME/levelsfyi-salary-scraper').call({
    companies: ['google', 'meta'],
    jobTitles: ['software-engineer'],
    maxItems: 100,
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();

API Example (Python)

from apify_client import ApifyClient
client = ApifyClient('YOUR_TOKEN')
run = client.actor('YOUR_USERNAME/levelsfyi-salary-scraper').call(run_input={
    'companies': ['google', 'meta'],
    'jobTitles': ['software-engineer'],
    'maxItems': 100,
})
items = client.dataset(run['defaultDatasetId']).list_items().items

API Example (cURL)

curl "https://api.apify.com/v2/acts/YOUR_USERNAME~levelsfyi-salary-scraper/runs" \
  -X POST \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_TOKEN" \
  -d '{"companies": ["google"], "jobTitles": ["software-engineer"], "maxItems": 100}'

Tips and tricks

• Start with a small maxItems (10-20) to test before running large scrapes
• Use residential proxies if you encounter blocking
• Combine multiple companies and job titles in a single run for efficiency
• Use the companies + jobTitles inputs instead of manually building URLs

FAQ

Q: Does this actor require login credentials? A: No. Levels.fyi salary data is publicly available.

Q: How fast is the scraping? A: Approximately 50-200 salary entries per minute depending on proxy speed and data density per page.

Q: What should I do if I get blocked? A: Switch to residential proxies in the Proxy Configuration settings and reduce max concurrency.

Q: What companies are supported? A: Any company listed on Levels.fyi. Use company slugs (e.g. "google", "meta", "amazon", "apple", "microsoft").

Is it legal to scrape Levels.fyi?

Web scraping of publicly available data is generally legal based on precedents like the LinkedIn v. HiQ Labs case. This actor only accesses publicly available data. Always review and respect the target site's Terms of Service and robots.txt. For more information, see Apify's blog on web scraping legality.

Limitations

• Only extracts publicly visible salary data (no paywalled content)
• Data accuracy depends on self-reported submissions to Levels.fyi
• Rate limiting may slow down very large scrapes
• Some salary entries may have incomplete fields (missing stock, bonus, etc.)

Changelog

• v0.1 (2026-04-23) -- Initial release