Senior Python Data Scraping Engineer
New
M
MindriftData Engineering
Italy. Rome, Metropolitan City of Rome Capital, Italy. Milan, Metropolitan City of Milan, Italy. Naples, Metropolitan City of Naples, Italy. Turin, Metropolitan City of Turin, Italy. Palermo, Metropolitan City of Palermo, ItalyContractSenior
SalaryUp to $40 per hour equivalent
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Job Details
- Languages
- English proficiency: Upper-intermediate (B2) or above
- Experience
- 5+ years
- Required Skills
- AWSDockerPythonSeleniumLangChain
Requirements
- At least 5+ years of relevant experience in data engineering, web scraping, automation, or software development.
- Strong experience in Python web scraping (BeautifulSoup, Selenium or similar), including dynamic content (JS, AJAX, infinite scroll) and APIs via proxies.
- Proven ability to extract data from complex structures (hierarchies, archived pages, inconsistent HTML).
- Solid background in data cleaning, normalization, and validation, delivering structured datasets (CSV, JSON, Google Sheets).
- Demonstrated experience handling anti-bot mechanisms and dynamic site structures at scale.
- Experience with cloud infrastructure (AWS or equivalent) and containerization (Docker) as part of real workflows.
- Hands-on experience with LLM frameworks (LangChain, OpenRouter, or similar) applied to automation tasks.
- Strong attention to detail and commitment to data accuracy.
- Self-directed work ethic with ability to troubleshoot independently.
- English proficiency: Upper-intermediate (B2) or above.
- Bachelor’s or Master’s Degree in Engineering, Applied Mathematics, Computer Science, or related technical fields is a plus.
Responsibilities
- Own end-to-end data extraction workflows across complex websites, ensuring complete coverage, accuracy, and reliable delivery of structured datasets.
- Leverage available tools and 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.
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