Real-Time Personalized Travel Recommendations Platform

As a growing player in the Travel & Tourism industry, we are committed to providing our customers with unique, tailored travel experiences. We aim to build a robust real-time platform that generates personalized travel recommendations based on user preferences, behaviors, and historical data. This involves architecting a data infrastructure that can handle event streaming and real-time data processing efficiently. The project will utilize Apache Kafka for data streaming, Spark for processing large datasets, and dbt for data transformations. We will also integrate with Snowflake or BigQuery for data warehousing capabilities. The data pipeline will be orchestrated using Apache Airflow, ensuring seamless data flow and observability across the system. The outcome will be a responsive recommendation engine that significantly improves the travel planning process, offering users relevant and timely suggestions. We're looking for skilled data engineers who can leverage these technologies to deliver a scalable and maintainable solution within 8-12 weeks.