Real-Time Language Learning Insights Platform Enhancement

As a growing startup in the Language Learning industry, we are committed to delivering personalized and adaptive learning experiences to our users. Our current challenge is the lack of real-time insights into user engagement and learning behaviors, which hampers our ability to iterate and optimize our platform quickly. We seek a data engineering expert to build a robust real-time data pipeline leveraging Apache Kafka for event streaming, Spark for processing, and Airflow for orchestration. The enhanced system should integrate seamlessly with our existing data infrastructure, which includes Snowflake and BigQuery, to enable real-time dashboards and analytics. By implementing a data mesh approach, we aim to democratize data access across our teams, enhance data observability, and support machine learning operations (MLOps) for continuous improvement. This project is critical as it will empower us to deliver dynamic, personalized content that caters to individual learning trajectories, thereby increasing user retention and satisfaction. The successful candidate will have experience with Apache Kafka, Spark, Airflow, and cloud data warehouses, and will be adept at building scalable, high-performance data solutions within a startup environment.