Web Scraping Specialist
Wynd Network
Remote
Posted on Wednesday, May 22, 2024
Web Scraping Specialist
$75k – $125k • 0.06% – 3.0%
Wynd is an early-stage startup empowering access to public web data. Wynd Labs enables access to public web data through decentralized data scraping tools such as our first product, Grass.
Grass is a network sharing application that allows users to sell their unused internet bandwidth.
Your day-to-day:
- Write, test, and refine code that extracts data from various online sources, ensuring reliability and efficiency.
- Perform data retrieval tasks, handling complexities such as pagination and dynamic content loaded with AJAX.
- Clean and format extracted data, ensuring it meets quality standards for further analysis or processing.
- Database management: Store and manage the scraped data in appropriate databases, optimizing for access speed and data integrity.
- Regularly monitor the scraping processes, identify and resolve any issues to maintain continuous data flow.
What experience you’ll need:
- Demonstrated ability to extract data from complex websites with minimal supervision, with a portfolio or examples of past projects.
Technical requirements:
- Proficiency in languages such as Python or JavaScript, with strong skills in libraries and frameworks like BeautifulSoup, Scrapy, or Selenium.
- Knowledge of asynchronous programming, multithreading, and distributed scraping.
- In-depth knowledge of HTML, CSS, JavaScript, and the Document Object Model (DOM).
- Experience with NoSQL databases (MongoDB, Cassandra), capable of designing efficient storage solutions and managing data integrity.
Bonus points:
- Ability to apply machine learning algorithms for data cleaning, categorization, or predictive analysis adds significant value.
- Experience with cloud services (AWS, Google Cloud, Azure) for deploying and managing scraping jobs at scale.
- Active participation in open-source projects related to web scraping, data processing, or similar fields.
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Our hiring process prioritizes a paid work trial over a traditional interview process.