Real-time Student Engagement Analytics for MOOC Platform

As a growing startup in the Online Learning & MOOCs industry, we aim to enhance our platform's ability to track and analyze student engagement in real-time. Our goal is to understand how students interact with course content to personalize learning experiences and improve retention rates. We seek an expert data engineer to design and implement a data architecture leveraging Apache Kafka for event streaming, Spark for processing, and Snowflake for storage. Utilizing Airflow and dbt, the proposed solution should facilitate seamless data workflow orchestration and transformation. This project will require integrating data from multiple sources into a centralized system enabling cross-functional stakeholders to access actionable insights. The solution should be scalable, ensuring high availability and quick response times, to accommodate our rapidly growing user base. The successful execution of this project will provide a competitive advantage by enhancing our content recommendation engine and supporting dynamic student learning pathways.