Python Selenium Django Backend Developer

We are looking for a skilled Python Selenium Django Backend Developer to join our team for a longterm fulltime position of more than 6 months.

Your role will involve:

• Django stack development
• API
• Database architecture
• Python scripting
• RESTful API development
• Developing maintaining and updating the backend architecture of our web application.
• Working closely with our frontend developers
• Ensure seamless integration of the user interface with the backend
• Responsibility for database management and architecture ensuring the efficient storage and retrieval of data.
  
  

We have multiple projects. One of them you can find here for your reference and as an EXAMPLE:

Required Skills:

• Experience with Python programming language.
• Proficiency in web scraping using Selenium Bs4 and requests.
• Knowledge of automation techniques.
• Familiarity with the Django web framework.
• Strong understanding of HTML and CSS for frontend development.
• Experience with database integration specifically Django models.
• Ability to handle duplicate data and merge records efficiently.
• Knowledge of Google search and web crawling techniques.
• Attention to detail and ability to handle complex scraping scenarios.
• Strong problemsolving skills and ability to work independently.
• Good communication skills to understand and implement the project requirements effectively.

Requirements for job scraper:

1. Programming Language: Python
The job scraper will be implemented using Python programming language.

2. Web Scraping: Selenium
Selenium will be used for web scraping tasks as it provides a powerful framework for automating browser interactions.

3. Web Framework: Django
The job scraper will be integrated into a Django web framework allowing for easy management and storage of scraped job data.

4. Frontend: HTML and CSS
HTML and CSS will be used to design and develop the user interface of the Django dashboard.

5. Platforms:
The bot will be capable of scraping jobs from multiple platforms including LinkedIn Indeed

6. User Input:
The user will be able to enter a filtered URL for the job page and specify the number of jobs they want to scrape.

7. Job Data Extraction:
The bot will extract the following information from each job listing:
> Job title
> Job location
> Company name
> Job description
> Source URL

8. Company Website Extraction:
After obtaining the company name the bot will search for it on Google and retrieve the first nonsponsored link. If the link belongs to a social website or information website like Quora or Wikipedia it will be skipped. Otherwise it will be included on the company website.

9. Email Address Extraction:
The bot will navigate to the company website URL and scrape the email address from the contact section. This email address will be included as the company email.

10 . Data Storage:
The scraped job data including company details will be saved to the Django model for easy management and retrieval.

11. Duplicate Job Handling:
The bot will check for duplicate job listings and merge them if the same job is found on multiple platforms. The source websites names will be included under the source website column.

Remote Work :

No