BuiltIn Jobs Scraper
Pricing
from $1.00 / 1,000 results
BuiltIn Jobs Scraper
Extract tech job listings effortlessly with the BuiltIn Jobs Scraper. Designed for speed and efficiency, this lightweight actor parses job data accurately from BuiltIn. For optimal performance and to avoid IP bans, the use of residential proxies is highly recommended.
Pricing
from $1.00 / 1,000 results
Rating
5.0
(4)
Developer
Shahid Irfan
Maintained by CommunityActor stats
5
Bookmarked
145
Total users
44
Monthly active users
3 days ago
Last modified
Categories
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Extract detailed job listings from BuiltIn with rich role metadata, salary information, structured location data, and application links. Collect clean BuiltIn job datasets for recruiting research, compensation analysis, market tracking, and job intelligence workflows.
Features
- Structured Job Records — Capture normalized BuiltIn job details with salary fields, employment type, benefits, and multi-location support
- Flexible Search Inputs — Search by keyword, location, category, or a custom BuiltIn jobs URL
- Automatic Pagination — Walk through multiple result pages until the requested result count is reached
- Clean Output — Removes duplicate records and omits empty values so datasets are easier to analyze
- Built For Analysis — Produces records that work well in spreadsheets, dashboards, internal tools, and data pipelines
Use Cases
Recruitment Intelligence
Track active hiring across BuiltIn companies and understand what kinds of roles are being filled. Compare employers by seniority, location spread, and application volume patterns.
Salary Benchmarking
Build compensation datasets with normalized salary minimums, maximums, and units. Use the data to compare pay ranges across roles, locations, and industries.
Job Market Research
Study how job demand shifts across categories, skills, and regions. Monitor which employers are posting repeatedly and where hiring is concentrated.
Company Monitoring
Follow hiring activity for specific employers or segments. Collect job URLs, company references, and application links for ongoing monitoring workflows.
Career Data Products
Use the dataset to power job trackers, analytics views, newsletters, or internal alerts. The output is suitable for export into downstream automation tools.
Input Parameters
| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
keyword | String | No | "software engineer" | Search keyword or role title |
location | String | No | — | Location filter for BuiltIn job search |
category | String | No | — | BuiltIn category alias to narrow the search |
startUrl | String | No | — | Custom BuiltIn jobs URL to use instead of keyword, location, and category |
results_wanted | Integer | No | 20 | Maximum number of jobs to collect |
max_pages | Integer | No | 20 | Maximum number of result pages to visit |
proxyConfiguration | Object | No | Apify Proxy | Proxy settings for more reliable collection at scale |
Output Data
Each item in the dataset contains:
| Field | Type | Description |
|---|---|---|
job_id | Integer | BuiltIn job identifier |
drupal_id | Integer | BuiltIn page identifier |
title | String | Job title |
company | String | Company name |
category | Array | Industry or category labels associated with the role |
location | String | Primary location summary |
locations_count | Integer | Number of listed job locations |
job_locations | Array | Structured location objects with city, state, country, and coordinates when available |
applicant_location_requirements | Array | Countries or regions where applicants may be located |
date_posted | String | Posting date |
valid_through | String | Listing expiry date when provided |
employment_type | String | Employment type such as full-time |
description_html | String | Full job description in HTML form |
description_text | String | Plain-text job description |
workplace_type | String | On-site, hybrid, or remote label when available |
workplace_type_enum | String | Normalized workplace type |
salary_range_short | String | Human-readable salary range |
salary_json_min | Number | Normalized salary minimum |
salary_json_max | Number | Normalized salary maximum |
salary_json_currency | String | Salary currency code |
salary_json_unit | String | Salary unit such as year or hour |
seniority | String | Experience level text |
job_benefits | Array | Benefit labels published with the role |
direct_apply | Boolean | Whether the listing supports direct apply |
apply_url | String | Application destination |
company_url | String | Company profile URL |
company_logo | String | Company logo URL |
company_overview | String | Company summary text when available |
url | String | BuiltIn job URL |
source | String | Source site name |
Usage Examples
Basic Search
Collect a small sample of software engineering jobs:
{"keyword": "software engineer","results_wanted": 20}
Location-Focused Search
Collect data for a specific location:
{"keyword": "data engineer","location": "New York","results_wanted": 50}
Category-Filtered Search
Focus on one BuiltIn category:
{"keyword": "ml engineer","category": "ai-machine-learning","results_wanted": 40}
Custom URL Search
Use a prepared BuiltIn search URL:
{"startUrl": "https://builtin.com/jobs?search=product+manager&location=Chicago","results_wanted": 30}
Sample Output
{"job_id": 7936464,"drupal_id": 7936464,"title": "Software Engineer","company": "Citadel","category": ["Information Technology","Software","Financial Services","Big Data Analytics"],"location": "Houston, Texas, USA","locations_count": 5,"job_locations": [{"street_address": "Bank of America Center 700 Louisiana St. Suite 4600","city": "Houston","state": "Texas","postal_code": "77002","country": "USA","latitude": 29.76078,"longitude": -95.36952}],"applicant_location_requirements": ["USA", "SGP", "GBR"],"date_posted": "2026-06-26","valid_through": "2026-07-26T14:25:08+00:00","employment_type": "FULL_TIME","description_text": "At Citadel, Software Engineers are responsible for building the systems that power every aspect of our investment process.","workplace_type": "In-Office","workplace_type_enum": "IN_OFFICE","salary_range_short": "150K-300K Annually","salary_json_min": 150000,"salary_json_max": 300000,"salary_json_currency": "USD","salary_json_unit": "YEAR","seniority": "Senior level","apply_url": "https://www.citadel.com/careers/details/software-engineer/","company_url": "https://builtin.com/company/citadel","url": "https://builtin.com/job/software-engineer/7936464","source": "builtin.com"}
Tips for Best Results
Start Small
- Begin with
20to validate search quality quickly - Increase volume after confirming the keyword or URL is returning the right roles
Use Focused Queries
- Specific role names generally produce cleaner results than broad keywords
- Combine keyword and location when you need narrower datasets
Control Pagination
- Use
max_pagesto keep large jobs searches predictable - Raise the cap only when you know the search has enough coverage
Improve Reliability
- For larger runs, use proxy configuration to reduce intermittent request failures
- Re-run narrow searches separately instead of one very broad request when consistency matters
Integrations
Connect your data with:
- Google Sheets — Review and share hiring datasets
- Airtable — Build searchable job databases
- Slack — Send alerts for new matching roles
- Webhooks — Forward records into internal systems
- Make — Automate enrichment and reporting workflows
- Zapier — Trigger follow-up actions from fresh job data
Export Formats
- JSON — For automation and application use
- CSV — For spreadsheets and lightweight analysis
- Excel — For reporting and business users
- XML — For system integrations that require it
Frequently Asked Questions
How many jobs can I collect?
You can collect as many matching jobs as BuiltIn exposes for the search query, subject to your results_wanted and max_pages limits.
Can I search by company?
Yes. You can use a BuiltIn jobs URL that already targets a specific company or search query.
Why are some optional fields missing?
BuiltIn does not publish every field on every role. The actor omits empty values rather than returning placeholders.
Does the actor remove duplicates?
Yes. Duplicate job URLs are filtered before records are written to the dataset.
Can I use proxies?
Yes. Proxy configuration is supported and recommended for larger or more frequent runs.
Can I schedule recurring runs?
Yes. Use Apify schedules to monitor job search results continuously.
Support
For issues or feature requests, contact support through the Apify Console.
Resources
Legal Notice
This actor is designed for legitimate data collection purposes. Users are responsible for ensuring compliance with BuiltIn terms and applicable laws when using the resulting data.