Built In Jobs Scraper

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Find and export public jobs from Built In for recruiting, sourcing, market research, and hiring-intelligence workflows.

The actor helps you collect job listings from Built In with filters for keywords, locations, remote preferences, categories, recency, and result limits. It returns clean dataset rows that can be exported to CSV, JSON, Excel, Google Sheets, databases, or your own workflow through the Apify API.

What does Built In Jobs Scraper do?

Built In Jobs Scraper collects public job listings from Built In and saves them as structured records.

It can help you answer questions like:

• Which companies are hiring for a role right now?
• Which remote jobs were recently posted?
• Which skills appear most often in a category?
• Which employers are active in a market?
• Which job pages should my team review first?

Who is it for?

Recruiters can monitor new roles in technical categories.

Sourcing teams can build lead lists of companies hiring for specific skills.

Sales teams can identify companies with hiring signals.

Job-market analysts can track demand by category, location, and recency.

Founders and operators can monitor competitors and adjacent companies.

Job seekers can collect public openings for personal research.

Why use this actor?

• ⚡ Fast setup with simple inputs
• 🧭 Built for public Built In job pages
• 📦 Structured dataset output
• 🔎 Keyword, category, location, and recency filters
• 🧾 Optional detail-page enrichment
• 🔁 Good for recurring monitoring runs
• 🧩 Works with Apify integrations and API clients

What data can it extract?

How much does it cost to scrape Built In jobs?

This actor uses pay-per-event pricing.

You pay a small start fee for each run and a per-result fee for every job listing saved.

The default prefill is intentionally small so your first run is inexpensive.

For large recurring monitoring jobs, increase maxItems gradually and review the dataset count after each run.

Quick start

1. Open the actor on Apify.
2. Enter a keyword such as python or data engineer.
3. Choose a remote preference.
4. Optionally add a Built In category slug.
5. Set maxItems.
6. Run the actor.
7. Export the dataset.

Input options

Start URLs

Use startUrls when you already have a Built In jobs page.

Examples:

• https://builtin.com/jobs/remote
• https://builtin.com/jobs/remote/dev-engineering
• https://builtin.com/jobs/remote/data-analytics

Keyword

Use keyword to search job titles, companies, skills, or other Built In search terms.

Examples:

• python
• data engineer
• security analyst
• product manager

Location

Use a Built In location slug if you want a location-specific jobs path.

Examples:

• chicago
• new-york
• san-francisco
• washington-dc

Leave it empty for broad remote searches.

Remote preference

Supported values:

• remote-or-hybrid
• remote
• hybrid
• any

Category

Common category slugs include:

• dev-engineering
• data-analytics
• sales
• marketing
• product
• design-ux
• cybersecurity-it
• customer-success
• finance
• hr
• operations
• legal
• project-management

Posted within days

Use postedWithinDays to focus on recent jobs.

Good starting values are 7, 14, or 30.

Include details

Turn includeDetails on to enrich each result with detail-page fields such as full description and posted date when available.

Turn it off for faster listing-only monitoring.

Example input

{
"keyword":"data engineer",
"category":"data-analytics",
"remotePreference":"remote-or-hybrid",
"postedWithinDays":14,
"maxItems":25,
"includeDetails":true
}

Example output

{
"title":"Forward Deployed Data Engineer - EU",
"companyName":"Datafold",
"jobUrl":"https://builtin.com/job/forward-deployed-data-engineer-eu/9827983",
"jobId":"9827983",
"location":null,
"remoteType":"TELECOMMUTE",
"description":"About Datafold...",
"postedDate":"2026-06-19",
"category":"Analytics",
"skills":["AI","Databricks","Snowflake"],
"salary":null,
"companyUrl":"https://builtin.com/company/datafold",
"scrapedAt":"2026-06-22T19:39:09.296Z"
}

Tips for best results

Start with a focused keyword.

Use category slugs for cleaner datasets.

Use postedWithinDays for monitoring recent hiring activity.

Use includeDetails: false when you only need fast top-level listings.

Use includeDetails: true when you need posted dates and fuller descriptions.

Keep maxItems low while testing a new filter combination.

Common workflows

Recruiting research

Run weekly searches for roles your team hires.

Export matching rows to CSV.

Review companies and job URLs.

Sales intelligence

Search for hiring signals in target categories.

Send company names and job URLs to a CRM enrichment workflow.

Use recurring runs to spot newly active accounts.

Market analysis

Track skills across data, engineering, product, and security roles.

Aggregate output by skill, company, category, and posted date.

Compare trends over time.

Integrations

You can send results to:

• Google Sheets
• Make
• Zapier
• Slack
• Airtable
• BigQuery
• Snowflake
• Webhooks
• Custom API consumers

API usage

Node.js

import{ ApifyClient }from'apify-client';
const client =newApifyClient({token: process.env.APIFY_TOKEN});
const run =await client.actor('fetch_cat/builtin-jobs-scraper').call({
keyword:'python',
remotePreference:'remote-or-hybrid',
maxItems:25,
});
console.log(run.defaultDatasetId);

Python

from apify_client import ApifyClient
client = ApifyClient('MY-APIFY-TOKEN')
run = client.actor('fetch_cat/builtin-jobs-scraper').call(run_input={
'keyword':'python',
'remotePreference':'remote-or-hybrid',
'maxItems':25,
})
print(run['defaultDatasetId'])

cURL

curl-X POST 'https://api.apify.com/v2/acts/fetch_cat~builtin-jobs-scraper/runs?token=MY-APIFY-TOKEN'\
-H'Content-Type: application/json'\
-d'{"keyword":"python","remotePreference":"remote-or-hybrid","maxItems":25}'

MCP usage

Use this actor through Apify MCP from Claude Desktop, Claude Code, or other MCP clients.

MCP server URL:

https://mcp.apify.com/?tools=fetch_cat/builtin-jobs-scraper

Claude Code setup:

$claude mcp add apify-builtin-jobs https://mcp.apify.com/?tools=fetch_cat/builtin-jobs-scraper

Claude Desktop JSON config:

{
"mcpServers":{
"apify-builtin-jobs":{
"url":"https://mcp.apify.com/?tools=fetch_cat/builtin-jobs-scraper"
}
}
}

Example prompts:

• "Run Built In Jobs Scraper for remote data engineer jobs and summarize the companies."
• "Find recent security analyst jobs on Built In and export the dataset."
• "Scrape 50 Built In product roles and group them by company."

Data quality notes

Built In displays different fields for different jobs.

Some jobs include salary ranges.

Some jobs do not show salary.

Some jobs include rich skills.

Some jobs only include basic category information.

Rows keep unavailable fields as null or empty arrays rather than inventing values.

Limits

The actor collects public pages that are available at run time.

If Built In returns fewer matching jobs than maxItems, the actor saves the available results.

Very broad searches can produce many pages, so use filters when possible.

FAQ

Can I scrape Built In jobs by keyword?

Yes. Use the keyword input with a job title, company, technology, or skill.

Can I monitor recent jobs only?

Yes. Use postedWithinDays with values such as 7, 14, or 30.

Troubleshooting

Why did I get fewer jobs than requested?

Your filters may have fewer public matches. Try removing postedWithinDays, broadening the keyword, or using a larger category.

Why are some fields null?

Built In does not display every field on every job. Salary, posted date, location, and detailed metadata can vary by listing.

Why is my location not working?

Use Built In style location slugs such as chicago, new-york, or washington-dc rather than long free-text strings.

Legality and responsible use

This actor is intended for public job-market research.

Use the data responsibly and respect applicable laws, platform terms, and privacy requirements.

Do not use exported data for spam, harassment, discrimination, or unlawful profiling.

Related scrapers

Explore other Apify actors from the same publisher for job-market, search, and business-data workflows:

• https://apify.com/fetch_cat/google-search-results-scraper

Changelog

0.1

Initial version with Built In job search, category filtering, recency filtering, optional detail enrichment, and structured dataset output.

Support

If a run does not return the data you expected, share the run input and a sample Built In URL when reporting the issue.

This helps reproduce the filter combination and improve extraction quality.

Dataset export

After the run finishes, open the dataset tab.

You can export results as JSON, CSV, Excel, XML, RSS, or HTML.

Use API dataset endpoints for automated pipelines.

Monitoring recommendations

For weekly monitoring, keep a stable keyword and category.

For daily monitoring, use postedWithinDays with a small value.

For broad market maps, run several focused searches instead of one very broad search.

Field reference summary

title is the job title.

companyName is the hiring company.

jobUrl is the canonical public job page.

jobId is the Built In listing identifier.

location is the available job location metadata.

remoteType is the work-location classification.

description is a listing description or enriched detail description.

postedDate is the source posted date when available.

category is Built In category text.

skills is a list of source skills.

salary is the visible compensation range.

companyUrl is the public Built In company page.

scrapedAt is the extraction timestamp.