Senior Python Data Scraping Engineer - AI-Human Workflow
New
United StatesContractSenior
SalaryUp to 30 USD per hour
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Job Details
- Languages
- English
- Experience
- 5+ years
- Required Skills
- AWSDockerPythonSeleniumJSONGoogle SheetsLangChain
Requirements
- Minimum 5+ years of experience in data engineering, web scraping, automation, or software development
- Strong hands-on experience with Python scraping frameworks such as BeautifulSoup, Selenium, or equivalent tools
- Proven ability to extract data from complex and inconsistent web structures, including dynamic and JavaScript-heavy sites
- Experience working with APIs, proxies, and anti-bot mitigation techniques
- Strong background in data cleaning, normalization, transformation, and validation
- Experience delivering structured datasets in formats such as CSV, JSON, or Google Sheets
- Familiarity with cloud environments such as AWS or equivalent platforms
- Experience using containerization tools like Docker in production workflows
- Exposure to LLM-based frameworks such as LangChain, OpenRouter, or similar automation tools
- Strong analytical mindset with exceptional attention to detail and data accuracy
- Ability to work independently, troubleshoot issues, and manage tasks without supervision
- Upper-intermediate or higher English proficiency (B2+ required)
Responsibilities
- Own end-to-end web scraping and data extraction workflows across complex and dynamic websites
- Build, maintain, and optimize Python-based scraping systems using tools such as BeautifulSoup, Selenium, and API integrations
- Extract structured datasets from dynamic content sources including JavaScript-rendered pages, AJAX calls, and infinite scroll interfaces
- Utilize internal tools (such as Apify and OpenRouter) alongside custom-built automation workflows to improve efficiency and scalability
- Ensure high data quality through validation checks, normalization processes, and cross-source consistency verification
- Handle large-scale scraping operations using batching, parallelization, and performance optimization techniques
- Monitor scraping stability and adapt quickly to changes in website structure or anti-bot mechanisms
- Deliver clean, structured datasets in formats such as CSV, JSON, or spreadsheet-based outputs
- Apply systematic quality control processes before final data delivery
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