Senior Python Data Scraping Engineer (Freelance)

Mindrift is a platform connecting specialists with AI projects from major tech innovators, focusing on unlocking the potential of Generative AI by leveraging real-world expertise globally. This role is for the Tendem project within Mindrift, involving hybrid AI + human data scraping workflows.

• Minimum 5+ years of relevant experience in data engineering, web scraping, automation, or software development.
• Bachelor’s or Master’s Degree in Engineering, Applied Mathematics, Computer Science, or related technical fields is a plus.
• Strong technical foundation with practical experience in scripting, automation, and AI-assisted workflows, including working confidently with LLMs.
• Extensive experience with Python web scraping tools such as BeautifulSoup, Selenium or similar, handling dynamic content like JS, AJAX, and infinite scroll, plus API access via proxies.
• Proven ability to extract data from complex structures including hierarchies, archived pages, and inconsistent HTML.
• Solid background in data cleaning, normalization, and validation, delivering structured datasets in formats like CSV, JSON, and Google Sheets.
• Experience handling anti-bot mechanisms and dynamic site structures at scale.
• Experience with cloud infrastructure (AWS or equivalent) and containerization (Docker).
• Hands-on experience with LLM frameworks (including LangChain, OpenRouter) applied to automation tasks.
• Strong attention to detail and commitment to data accuracy.
• Ability to work independently with a self-directed work ethic.
• English proficiency at Upper-intermediate level (B2) or higher.

Nice to have:

• A link to GitHub portfolio.

• Own end-to-end data extraction workflows across complex websites, ensuring complete coverage, accuracy, and reliable delivery of structured datasets.
• Leverage internal tools (Apify, OpenRouter) alongside custom workflows to accelerate data collection, validation, and task execution while meeting defined requirements.
• Ensure reliable extraction from dynamic and interactive web sources, adapting approaches as needed to handle JavaScript-rendered content and changing site behavior.
• Enforce data quality standards through validation checks, cross-source consistency controls, adherence to formatting specifications, and systematic verification prior to delivery.
• Scale scraping operations for large datasets using efficient batching or parallelization, monitor failures, and maintain stability against minor site structure changes.