# Built In Tech Salaries, by Title, Metro Area and Experience (`gubidonius/builtin-salaries`) Actor

US tech salaries from builtin.com for 200 titles, nationally, remote or in any of 50 metro areas: average, median, range, percentiles, the histogram, and breakdowns by experience, gender and company size. Every row carries how many people answered.

- **URL**: https://apify.com/gubidonius/builtin-salaries.md
- **Developed by:** [Gregory Bolshakov](https://apify.com/gubidonius) (community)
- **Categories:** Jobs, Business, Lead generation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

Pay per event

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## Built In Tech Salaries, by Title, Metro Area and Experience

The salary pages on builtin.com: for each of 200 tech job titles, nationally, remote, or
in any of 50 US metro areas, the average base, additional cash and total compensation,
the median and range, the percentiles, the whole histogram, and the averages by years of
experience, by gender and by company size. No key and no login.

### What the pages hide

Two things, both on every page and both visible only when you look at two pages side by
side.

The national page leaves the percentiles empty. Data Engineer in the US reports a median
and a range and empty strings for the 10th, 25th, 75th and 90th percentiles. The same
title in Austin reports all four. Empty is published as null, never as zero, and
`percentilesPublished` says which kind of page a row came from.

A title with no respondent in a place still gets a page, and that page prints $0 for the
average, the median, the minimum and the maximum. Blockchain Developer in Austin did on
11 September 2026. Zero is not a salary. Such a page is listed in `RUN_SUMMARY` under
`pagesWithoutRespondents` and no row is written for it.

Between those two sits the small-sample case: a page with one or two respondents prints
an average, a minimum and a maximum that are the same one or two numbers. `respondents`
on every row is the histogram's own count, so a buyer can see a $217,500 average for
Blockchain Developer, Remote, rests on two answers.

### What a row is

One title in one location. Ask for `US` and `Austin, TX` together and you get two rows
for the same title, and the national row also carries `topCities`, the best paying metro
areas for that title with their gap to the national average.

### Billing

Two events: a start fee charged only once a row is returned, and a per-row fee charged
after each row is written. A title the pages do not know, or a page with no respondents,
costs nothing.

# Actor input Schema

## `jobTitles` (type: `array`):

Titles from the salary pages' own list of 200, by name or slug: Data Engineer, software-engineer, Product Manager. A title the pages do not have is reported with the nearest real names rather than guessed.

## `allTitles` (type: `boolean`):

Read every title the pages list instead of the ones above, up to maxTitles, within the categories below when any are given.

## `categories` (type: `array`):

Engineering, Data & Analytics, Sales and the rest of the 19. With no titles named, every title in these categories is read.

## `locations` (type: `array`):

US for the national figures, Remote, or any of the 50 metro areas as the pages name them: Austin, TX or austin-tx, New York City, NY, San Francisco, CA. One row per title and location. A national page leaves the percentiles empty and a city page fills them, so ask for both when you want both.

## `maxTitles` (type: `integer`):

Most titles to read, applied after the list is resolved and to allTitles.

## `maxResults` (type: `integer`):

Most rows to return across titles and locations, and the most you will be charged for.

## Actor input object example

```json
{
  "jobTitles": [
    "Data Engineer",
    "Software Engineer"
  ],
  "allTitles": false,
  "categories": [],
  "locations": [
    "US"
  ],
  "maxTitles": 50,
  "maxResults": 500
}
```

# Actor output Schema

## `results` (type: `string`):

No description

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "jobTitles": [
        "Data Engineer",
        "Software Engineer"
    ],
    "allTitles": false,
    "categories": [],
    "locations": [
        "US"
    ],
    "maxTitles": 50,
    "maxResults": 500
};

// Run the Actor and wait for it to finish
const run = await client.actor("gubidonius/builtin-salaries").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "jobTitles": [
        "Data Engineer",
        "Software Engineer",
    ],
    "allTitles": False,
    "categories": [],
    "locations": ["US"],
    "maxTitles": 50,
    "maxResults": 500,
}

# Run the Actor and wait for it to finish
run = client.actor("gubidonius/builtin-salaries").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "jobTitles": [
    "Data Engineer",
    "Software Engineer"
  ],
  "allTitles": false,
  "categories": [],
  "locations": [
    "US"
  ],
  "maxTitles": 50,
  "maxResults": 500
}' |
apify call gubidonius/builtin-salaries --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,gubidonius/builtin-salaries"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/qsjneyawzeYkxLee1/builds/VumWCdujVaRYhKxml/openapi.json