4 days ago
Remote, Spain +3 moreSenior
Responsibilities
- Own end-to-end data extraction workflows across complex websites and deliver complete, accurate, structured datasets.
- Use custom workflows and available tools to accelerate data collection, validation, and task execution.
- Extract data from dynamic and interactive sources, including JavaScript-rendered content, while adapting to changing site behavior.
- Apply validation, cross-source consistency checks, formatting controls, and systematic verification to ensure data quality.
- Scale scraping operations through batching or parallelization, monitor failures, and maintain stability against minor site structure changes.
Requirements
- At least 5 years of relevant experience in data engineering, web scraping, automation, or software development.
- Strong Python web scraping experience, including BeautifulSoup, Selenium or similar tools, dynamic content, and APIs via proxies.
- Ability to extract data from complex structures such as hierarchies, archived pages, and inconsistent HTML.
- Experience with data cleaning, normalization, validation, and delivery of structured CSV, JSON, or Google Sheets datasets.
- Experience handling anti-bot mechanisms and dynamic site structures at scale.
- Experience with AWS or equivalent cloud infrastructure and Docker containerization in real workflows.
- Hands-on experience with LLM frameworks such as LangChain or OpenRouter for automation tasks.
- Upper-intermediate English proficiency at B2 level or above.
- A GitHub link is a plus; strong attention to detail and independent troubleshooting ability are expected.
- A bachelor's or master's degree in engineering, applied mathematics, computer science, or a related technical field is a plus.
Benefits
- Remote freelance work with part-time participation estimated at 10–20 hours per week during active project phases.
- Compensation of up to $40 per hour equivalent, depending on level and pace of contribution.
- Workload is project-dependent and not guaranteed outside active phases.
Tech Stack
Categories
Data Engineering
