Python Data Scraping Engineer

Jobgether
4 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior
Compensation
€ 62K

Job location

Remote

Tech stack

JavaScript
Artificial Intelligence
AJAX
Amazon Web Services (AWS)
Business Analytics Applications
Big Data
Spreadsheets
Data Cleansing
Information Engineering
Web Scraping
Data Mining
Github
JSON
Python
Performance Tuning
Selenium
Software Engineering
Cloud Platform System
Large Language Models
Containerization
Dynamic Content
Data Delivery
Api Design
Api Management
Docker

Job description

This role is designed for a highly technical professional who specializes in building robust, scalable, and accurate web data extraction systems within a hybrid AI-human workflow environment. You will work on complex scraping challenges involving dynamic websites, large datasets, and structured data delivery at scale. The position combines hands-on engineering with problem-solving, requiring strong Python expertise and the ability to adapt scraping strategies to evolving web environments. You will collaborate with AI-driven agents while ensuring human-level accuracy, validation, and quality control. This is a remote freelance opportunity where independence, precision, and technical creativity are essential. Your work will directly contribute to building reliable datasets that support advanced AI and analytics applications. Accountabilities:

  • 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.

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).
  • Nice to have: GitHub portfolio showcasing relevant scraping or automation projects.

Benefits & conditions

  • Fully remote freelance opportunity with flexible working schedule.
  • Work on cutting-edge hybrid AI + human systems in a fast-growing technical field.
  • Opportunity to collaborate with advanced AI tools and automation frameworks.
  • Competitive compensation of up to $30/hour depending on experience and performance.
  • Performance-based bonuses rewarding quality and consistency.
  • Exposure to complex real-world data extraction and AI-driven workflows.
  • High autonomy with the ability to choose your working pace and environment.
  • Opportunity to build highly valuable expertise in AI-assisted data engineering.

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