Real-Time Data Pipeline Enhancement for Personalized Travel Experiences

As a growing travel agency, we recognize the critical need to provide our customers with personalized and timely travel recommendations. Currently, our data pipeline is limited to batch processing, which restricts our ability to deliver real-time insights. We are looking for a skilled data engineer to design and implement an enhanced data pipeline that supports real-time analytics and dynamic data integration. The upgraded system should utilize Apache Kafka for event streaming, Spark for processing, and Snowflake or BigQuery for data warehousing. Our goal is to transform customer interactions by delivering personalized travel itineraries, special offers, and relevant content as they interact with our platform. This project will involve setting up a data mesh architecture that integrates various data sources across the organization, improving data observability, and implementing MLOps practices to streamline data operations. By doing so, we aim to increase customer engagement and boost conversion rates.