Job description

Mindrift is looking for highly skilled Senior Python Data Scraping Engineers to join the Tendem project and drive specialized data scraping workflows within our hybrid AI + human system.
In this role, as an AI Pilot – that’s how we refer to this role at Mindrift – you’ll collaborate with Tendem Agents that handle repetitive tasks, while you provide critical thinking, domain expertise, and quality control to deliver accurate and actionable results.
This part-time remote opportunity is ideal for technical professionals with hands-on experience in web scraping, data extraction and processing.
What We Do The Mindrift platform connects specialists with AI projects from major tech innovators.
Our mission is to unlock the potential of Generative AI by tapping into real-world expertise from across the globe.
This is a freelance role for a Tendem project.
As a Senior Python Data Scraping Engineer , you'll handle data scraping tasks requiring technical precision for web extraction and processing, utilizing various tools such as our provided Apify and OpenRouter alongside your own resourceful approaches.
Key Responsibilities: Own end-to-end data extraction workflows across complex websites, ensuring complete coverage, accuracy, and reliable delivery of structured datasets.
Leverage internal tools (Apify, OpenRouter) alongside 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.
Requirements: At least 5+ years of relevant experience in data engineering, web scraping, automation, or software development (required).
Bachelor’s or Master’s Degree in Engineering, Applied Mathematics, Computer Science, or related technical fields is a plus.
Candidates should have a strong technical foundation and practical experience with scripting, automation, and AI-assisted workflows.
We are looking for specialists who can solve non-trivial problems, work confidently with LLMs, and systematically collect, structure, and validate data from diverse sources.
A methodical, detail-oriented approach and the ability to work independently are essential.
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 A link to GitHub is a plus English proficiency: Upper-intermediate (B2) or above (required) Project time expectations For this project, tasks are estimated to require around 10–20 hours per week during active phases, based on project requirements.
This is an estimate, not a guaranteed workload, and applies only while the project is active.
Compensation On this project, contributors can earn up to $37 per hour equivalent , depending on their level and pace of contribution.
Compensation varies across projects depending on scope, complexity, and required expertise.
Please note that other projects on the platform may offer different earning levels based on their requirements.