Japan Dev Scraper helps you collect structured job listings focused on tech opportunities in Japan, all in one clean dataset. It’s designed to save time, reduce manual research, and give you clear visibility into roles that often include relocation support.
Whether you’re hiring, job hunting, or analyzing the market, this scraper turns scattered listings into usable insights.
Created by Bitbash, built to showcase our approach to Scraping and Automation!
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This project extracts job listings from Japan-focused tech job boards and organizes them into structured, easy-to-use data. It solves the problem of manually browsing dozens of listings by automating collection and filtering.
It’s built for recruiters, job seekers, analysts, and teams who need reliable job market data without noise.
- Collects detailed job postings centered on Japan-based companies
- Supports filtering by company name, job title, and skill focus
- Captures relocation-related information where available
- Outputs clean, structured data ready for analysis or integration
| Feature | Description |
|---|---|
| Targeted job collection | Gathers tech job listings focused on Japan-based roles |
| Advanced filtering | Filter results by company, title, or custom criteria |
| Rich job details | Extracts descriptions, requirements, and company context |
| Relocation insights | Identifies roles that support international candidates |
| Scalable extraction | Handles large result sets with consistent performance |
| Field Name | Field Description |
|---|---|
| company | Name of the hiring company |
| title | Job title as listed |
| location | Job location or remote status |
| description | Full job description text |
| requirements | List of required skills or experience |
| relocation | Indicates whether relocation support is offered |
[
{
"company": "TableCheck",
"title": "Senior Project Manager",
"location": "Tokyo, Japan",
"description": "Responsible for leading project teams and ensuring successful project delivery.",
"requirements": [
"5+ years of project management experience",
"Experience in agile methodology",
"Excellent communication skills"
],
"relocation": true
},
{
"company": "Exawizards",
"title": "Senior Cloud Security Engineer",
"location": "Remote / Tokyo, Japan",
"description": "Design and implement cloud security solutions.",
"requirements": [
"3+ years of experience in cloud security",
"Knowledge of AWS and Azure",
"Strong analytical skills"
],
"relocation": true
}
]
Japan Dev Scraper/
├── src/
│ ├── main.py
│ ├── collectors/
│ │ ├── jobs_collector.py
│ │ └── filters.py
│ ├── parsers/
│ │ └── job_parser.py
│ ├── outputs/
│ │ └── exporter.py
│ └── config/
│ └── settings.example.json
├── data/
│ ├── sample_input.json
│ └── sample_output.json
├── requirements.txt
└── README.md
- Recruitment agencies use it to track Japan-based tech roles, so they can match candidates faster.
- Job seekers use it to discover relocation-friendly positions without manual searching.
- Tech companies use it to analyze competitor hiring trends and in-demand skills.
- Market researchers use it to study employment patterns in Japan’s tech ecosystem.
- HR teams use it to build internal datasets for workforce planning.
What kind of roles does this scraper focus on? It primarily targets technology and software-related roles listed by companies hiring in Japan, including remote-friendly and relocation-supported positions.
Can I limit results to specific companies or titles? Yes, the input configuration allows you to filter by company names, job titles, and result limits.
Is this suitable for large-scale data collection? It’s designed to handle hundreds of listings efficiently while maintaining structured, consistent output.
What format is the output delivered in? The scraper outputs structured JSON, making it easy to store, analyze, or integrate with other systems.
Primary Metric: Processes up to 100 job listings per run with consistent extraction accuracy.
Reliability Metric: Maintains a stable success rate across repeated runs with minimal failed records.
Efficiency Metric: Optimized data parsing keeps memory usage low during larger extractions.
Quality Metric: High data completeness, with full job descriptions and requirements captured for the majority of listings.
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