Maritime Job Board Scraping
Budget: £20 – £250 GBP
I’m building an internal dashboard that tracks every maritime-related vacancy published online and I need a robust, repeatable scraping solution. My scope is broad: I want coverage of all major job boards that regularly post roles for the shipping, offshore, and port-services sectors. Because I don’t have a definitive site list yet, I’ll count on you to recommend the platforms you know are rich in maritime listings—think the big global boards as well as any niche maritime career portals you’re aware of.
From each posting, I must capture the following fields:
• Job title and full description
• Company name plus location (city, state/region, country)
• Employment type and any salary or rate information available
Your scraper should store results in a clean, normalized CSV (or optionally a relational DB if you prefer) and be easy for me to rerun on demand. I’m comfortable with Python, so a script leveraging requests/BeautifulSoup, Scrapy, or Playwright makes sense, but if another stack delivers better reliability feel free to suggest it.
Key expectations
• Site recommendations presented first for my approval before you start coding
• Respect robots.txt, add configurable request delays, and build basic anti-block measures (user-agent rotation, retries)
• Clear documentation explaining how to set up and execute the scraper
Once the first sweep is complete and the data checks out, we can discuss an automated schedule or incremental updates.
From each posting, I must capture the following fields:
• Job title and full description
• Company name plus location (city, state/region, country)
• Employment type and any salary or rate information available
Your scraper should store results in a clean, normalized CSV (or optionally a relational DB if you prefer) and be easy for me to rerun on demand. I’m comfortable with Python, so a script leveraging requests/BeautifulSoup, Scrapy, or Playwright makes sense, but if another stack delivers better reliability feel free to suggest it.
Key expectations
• Site recommendations presented first for my approval before you start coding
• Respect robots.txt, add configurable request delays, and build basic anti-block measures (user-agent rotation, retries)
• Clear documentation explaining how to set up and execute the scraper
Once the first sweep is complete and the data checks out, we can discuss an automated schedule or incremental updates.
Related categories:
Python
Data Processing
Web Scraping
Software Architecture
Data Mining
Scrapy
Data Extraction
BeautifulSoup