Levels.fyi Salary Scraper

Extract structured compensation samples from public Levels.fyi salary pages.

Use this actor to collect salary benchmarks by company, role, level, location, experience, base pay, stock, bonus, and total compensation.

What does Levels.fyi Salary Scraper do?

Levels.fyi Salary Scraper reads public company salary pages such as https://www.levels.fyi/companies/google/salaries/software-engineer and turns the embedded compensation records into clean dataset rows.

It is designed for compensation research, recruiting intelligence, salary benchmarking, and talent-market analysis.

The actor uses HTTP extraction from the page data already delivered to the browser. It does not require a login for public salary pages.

Who is it for?

• 💼 Recruiters comparing offer competitiveness across target employers.
• 📊 Compensation analysts building pay bands from market signals.
• 🧑‍💼 HR and People Ops teams reviewing leveling and location trends.
• 🏢 Startup founders planning engineering salary budgets.
• 🔎 Researchers studying total compensation by level, role, and geography.
• 🧰 Data teams feeding salary records into BI dashboards or spreadsheets.

Why use this Levels.fyi scraper?

Levels.fyi pages are useful, but manual copy-paste is slow and inconsistent.

This actor gives you repeatable exports with normalized fields:

• company and role context
• level and focus tag
• years of experience
• years at company
• offer date
• location identifiers
• base salary
• total compensation
• stock grant value
• bonus value
• level average compensation
• source URL and scrape timestamp

Data you can extract

Field	Description
uuid	Public sample identifier when present
company	Company name
companySlug	Levels.fyi company slug
role	Salary sample title
jobFamily	Job family shown on the page
jobFamilySlug	Job-family slug from the URL/page data
level	Company level, for example L3 or L5
focusTag	Specialization tag when available
location	Location label
dmaId	Location DMA identifier when present
countryId	Country identifier when present
yearsOfExperience	Candidate experience at offer time
yearsAtCompany	Tenure at the company
yearsAtLevel	Tenure at level when present
offerDate	Offer/sample date
baseSalary	Base salary amount
totalCompensation	Total yearly compensation
avgAnnualStockGrantValue	Annualized stock/equity value
avgAnnualBonusValue	Annualized bonus value
currency	Currency code inferred from the page/sample
gender	Gender field if present in the public sample
employmentType	Employment type when present
workArrangement	Remote/hybrid/on-site signal when present
levelSampleCount	Number of samples in the level band
levelAverageBaseSalary	Average base salary for the level
levelAverageStockGrant	Average stock value for the level
levelAverageBonus	Average bonus value for the level
levelAverageTotalCompensation	Average total compensation for the level
levelPageUrl	Public level-specific page URL
sourceUrl	Salary page scraped
scrapedAt	ISO timestamp of extraction

How much does it cost to scrape Levels.fyi salary data?

The actor uses pay-per-event pricing:

• $0.005 start fee per run
• formula-derived tiered per-result pricing for each salary sample saved
• BRONZE per-result price: $0.0001 per salary sample (platform minimum adjustment above the formula floor)

You only pay for records produced. Use a small maxSamplesPerPage during testing, then increase it for production benchmarking.

How to use this actor

1. Open the actor on Apify.
2. Add one or more public Levels.fyi salary URLs.
3. Optionally add company slugs and job-family slugs.
4. Set maxSamplesPerPage.
5. Run the actor.
6. Export results as JSON, CSV, Excel, or via the Apify API.

Input options

Levels.fyi salary page URLs

Use startUrls when you already know exact pages.

Example:

{
  "startUrls": [
    { "url": "https://www.levels.fyi/companies/google/salaries/software-engineer" }
  ],
  "maxSamplesPerPage": 50
}

Company and job-family slugs

Use slugs to generate URLs automatically.

{
  "companySlugs": ["google", "meta", "microsoft"],
  "jobFamilySlugs": ["software-engineer", "product-manager"],
  "maxSamplesPerPage": 100
}

Raw sample JSON

Enable includeRawSample only if you need the original embedded object for custom mapping.

Output example

{
  "company": "Google",
  "role": "Software Engineer",
  "level": "L4",
  "location": "Los Angeles, CA",
  "yearsOfExperience": 14,
  "yearsAtCompany": 5,
  "baseSalary": 180000,
  "totalCompensation": 220000,
  "avgAnnualStockGrantValue": 40000,
  "avgAnnualBonusValue": 0,
  "currency": "USD",
  "sourceUrl": "https://www.levels.fyi/companies/google/salaries/software-engineer",
  "scrapedAt": "2026-05-26T00:00:00.000Z"
}

Tips for better results

• Start with one URL and a low sample limit.
• Use public company salary pages, not login-only pages.
• Combine company slugs and job families for batch research.
• Keep includeRawSample disabled unless you need debugging details.
• Export CSV for spreadsheet review.
• Export JSON for data pipelines.

Integrations

Use the dataset with:

• Google Sheets or Excel compensation models.
• Airtable recruiting research bases.
• BigQuery, Snowflake, or Postgres salary warehouses.
• HR analytics dashboards.
• Recruiting market intelligence workflows.
• Apify webhooks for scheduled refreshes.

API usage

Node.js

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('automation-lab/levels-fyi-salary-scraper').call({
  startUrls: [{ url: 'https://www.levels.fyi/companies/google/salaries/software-engineer' }],
  maxSamplesPerPage: 50,
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items.slice(0, 3));

Python

from apify_client import ApifyClient
import os

client = ApifyClient(os.environ['APIFY_TOKEN'])
run = client.actor('automation-lab/levels-fyi-salary-scraper').call(run_input={
    'startUrls': [{'url': 'https://www.levels.fyi/companies/google/salaries/software-engineer'}],
    'maxSamplesPerPage': 50,
})
items = client.dataset(run['defaultDatasetId']).list_items().items
print(items[:3])

cURL

curl -X POST "https://api.apify.com/v2/acts/automation-lab~levels-fyi-salary-scraper/runs?token=$APIFY_TOKEN" \
  -H 'Content-Type: application/json' \
  -d '{"companySlugs":["google"],"jobFamilySlugs":["software-engineer"],"maxSamplesPerPage":50}'

MCP usage

Connect the actor through Apify MCP:

https://mcp.apify.com/?tools=automation-lab/levels-fyi-salary-scraper

Claude Code setup:

$claude mcp add apify-levels-fyi-salary "https://mcp.apify.com/?tools=automation-lab/levels-fyi-salary-scraper"

Claude Desktop JSON config:

{
  "mcpServers": {
    "apify-levels-fyi-salary": {
      "url": "https://mcp.apify.com/?tools=automation-lab/levels-fyi-salary-scraper"
    }
  }
}

Example prompts:

• "Scrape Google software engineer salary samples from Levels.fyi and summarize median total compensation."
• "Compare public Levels.fyi salary samples for Google and Microsoft software engineers."
• "Export Levels.fyi product manager salary records as CSV-ready data."

Scheduling

Schedule daily, weekly, or monthly runs in Apify Console when you need fresh compensation data.

For salary benchmarking, monthly refreshes are often enough.

For recruiting campaigns, weekly refreshes can catch new samples sooner.

Data quality notes

The actor extracts public user-submitted compensation samples. Treat them as market signals, not payroll-certified data.

Use filters and aggregation to reduce outlier impact.

Compare multiple companies, levels, and locations before making compensation decisions.

FAQ

Is Levels.fyi Salary Scraper free to try?

You can run a small test with a low maxSamplesPerPage value to estimate output volume and cost before scaling up.

Can I scrape multiple companies in one run?

Yes. Add multiple company slugs and job-family slugs, or provide multiple exact salary page URLs.

Troubleshooting

The actor returned no results

Check that the URL is a public salary page using the /companies/{company}/salaries/{job-family} pattern.

I received fewer records than expected

Levels.fyi may expose a limited number of public samples on a page. Increase maxSamplesPerPage, add more pages, or use more company/job-family combinations.

Some fields are null

Not every public sample includes every attribute. Null values mean the field was absent in the page data.

Legality and responsible use

This actor extracts publicly available page data. You are responsible for using exported data in a way that complies with applicable laws, contracts, privacy rules, and Levels.fyi terms.

Do not use salary data to make discriminatory decisions.

Do not attempt to scrape private, login-only, or access-controlled data.

Related scrapers

Other Automation Lab actors that may complement this workflow:

• https://apify.com/automation-lab/linkedin-jobs-scraper
• https://apify.com/automation-lab/indeed-scraper
• https://apify.com/automation-lab/google-maps-lead-finder
• https://apify.com/automation-lab/company-employee-scraper

Changelog

0.1

Initial actor for public Levels.fyi salary sample extraction.

Support

If a public salary URL fails, include the input URL, run ID, and expected company/role in your support request.

Summary

Levels.fyi Salary Scraper helps teams turn public compensation pages into structured salary datasets for benchmarking, recruiting, and workforce planning.