How to scrape jobs data from Doda using the Minexa.ai extension

Collecting job listing data from Doda, one of Japan's largest job platforms, by hand is slow and breaks down quickly once you need more than a handful of records. Each company card on Doda surfaces multiple job references, salary structures, and linked detail pages, and copying that manually across hundreds of pages is not a realistic workflow.

This guide walks through exactly how to extract that data using the Minexa.ai Chrome extension, no code required, starting from the company search listing page at doda.jp/DodaFront/View/CompanySearch/j_job__1/.

Watch the full tutorial first, then follow the steps below:

https://www.youtube.com/watch?v=uc82WjR2F10

Install the Minexa.ai extension and open it from your Chrome toolbar once it is installed.

Starting on the right page

Navigate to the Doda company search listing page. This is the page that shows multiple company cards, each containing job references, salary details, and links to individual postings.

Once the page has loaded, open the Minexa.ai extension from your toolbar. The popup will show a confirmation prompt asking whether you are on the correct page to begin extraction.

Pagination detection

Minexa.ai automatically detects how Doda paginates its results. You will see the pagination structure listed in the extension panel. Confirm it and continue, and Minexa.ai will handle all subsequent pages without any additional input from you.

After confirming pagination, you will be asked whether you want to scrape the list only, or also follow each listing link to extract detail page data. For this workflow, scraping the list is sufficient to capture all key fields per company card.

Container selection and field discovery

Minexa.ai highlights the repeating card container on the page automatically. Each card corresponds to one row in your final dataset. You confirm the selection and the extension creates the scraper configuration.

Once the container is confirmed, all extracted data points become visible in the extension panel. You can navigate through each field using the prev and next controls to review what was found before running the full job.

What the extracted data looks like

Each row in the output corresponds to one company card on Doda. Here is a sample of what two records look like after extraction:

[
  {
    "company_name": "コナミグループ株式会社",
    "company_name_2": "株式会社ゲームフリーク",
    "job_id": "3014916456",
    "job_id_2": "3015311470",
    "job_id_3": "3015311535",
    "job_link": "https://doda.jp/DodaFront/View/JobSearchDetail/j_jid__3014916456/",
    "job_salary_description": "予定年収: 527万円～638万円 / 月給制 / 月額: 300,000円～362,000円",
    "related_job_id": "3015277766",
    "related_job_link": "https://doda.jp/DodaFront/View/JobSearchDetail/j_jid__3015311470/"
  },
  {
    "company_name": "森永製菓 株式会社",
    "company_name_2": "株式会社野村総合研究所",
    "job_id": "3014968624",
    "job_id_2": "3014996447",
    "job_id_3": "3014815223",
    "job_link": "https://doda.jp/DodaFront/View/JobSearchDetail/j_jid__3014968624/",
    "job_salary_description": "予定年収: 500万円～700万円 / 月給制 / 月額: 240,000円～320,000円",
    "related_job_id": "3014680696",
    "related_job_link": "https://doda.jp/DodaFront/View/JobSearchDetail/j_jid__3014996447/"
  }
]

The job_salary_description field returns a full Japanese-language salary block per listing, including the expected annual income range, pay structure type (monthly or annual), base monthly salary, overtime allowance status, and supplementary notes about how final compensation is determined. This is the complete text as it appears in the page source, not a parsed or summarised version.

The related_job_id and related_job_link fields expose secondary job references tied to the same company card. Each card on Doda can surface up to three separate job IDs and their corresponding detail page URLs, meaning one row in your dataset can give you direct access to multiple open roles at the same company without visiting any individual page.

The job_id_3 field captures a third numeric job identifier per card. This ID does not appear in the primary job_link field, so it would be invisible to anyone only collecting the main listing URL. Having it in the dataset means you can reference or track that role independently.

Running the job and exporting

Once the job completes, your data is ready to export as Excel, JSON, or directly to Google Sheets. Every company card across all paginated pages is captured as a structured row, with each field in its own column.

You can also set the job to run on a schedule so your Doda dataset stays current without manual effort each time.

If you want to go further with job market research using structured web data, the post on how to scrape jobs data from Apna covers a related extraction workflow worth reading alongside this one.