4 days ago
Remote, United StatesSenior
Responsibilities
- Own end-to-end data-extraction workflows across complex websites and deliver accurate, structured datasets.
- Use custom workflows and tools to accelerate data collection, validation, and task execution.
- Extract reliably from dynamic and interactive sources, including JavaScript-rendered content, AJAX, and infinite-scroll pages.
- Apply validation, cross-source consistency checks, formatting controls, and systematic verification to maintain data quality.
- Scale scraping operations through batching or parallelization, monitor failures, and maintain stability against minor site changes.
- Handle anti-bot mechanisms and dynamic site structures at scale.
- Use cloud infrastructure, containerization, and LLM frameworks in automation workflows.
Requirements
- At least 5 years of relevant experience in data engineering, web scraping, automation, or software development.
- Strong Python web-scraping experience with BeautifulSoup, Selenium, or similar tools, including dynamic content and APIs via proxies.
- Ability to extract data from hierarchies, archived pages, inconsistent HTML, and other complex structures.
- Experience with data cleaning, normalization, validation, and delivery in CSV, JSON, or Google Sheets.
- Experience with AWS or equivalent cloud infrastructure and Docker in real workflows.
- Hands-on experience with LLM frameworks such as LangChain, OpenRouter, or similar for automation tasks.
- Upper-intermediate English proficiency at B2 level or above.
- Strong attention to detail, independent troubleshooting ability, and a self-directed work ethic.
- A GitHub link is a plus.
- A bachelor's or master's degree in engineering, applied mathematics, computer science, or a related technical field is a plus.
Benefits
- Remote, part-time freelance work.
- Estimated workload of approximately 10–20 hours per week during active project phases, with no guaranteed workload.
- Compensation of up to $45 per hour equivalent, depending on level and pace of contribution.
Tech Stack
Categories
Data Engineering
