Real-Time Data Pipeline Implementation for Enhanced Travel Booking Insights

In the competitive Travel & Tourism industry, understanding customer behavior in real-time is crucial for enhancing service offerings and boosting sales. Our company is experiencing rapid growth and requires a state-of-the-art data engineering solution to keep pace with the evolving market demands. The project involves designing a comprehensive real-time data pipeline that aggregates data from multiple booking platforms and customer interaction touchpoints. By using Apache Kafka for event streaming and Spark for processing, the pipeline should deliver insights with minimal latency. Additionally, the data infrastructure will implement a data mesh architecture using tools like dbt and Apache Airflow to ensure data is accessible, governed, and observable. Integration with Snowflake or BigQuery will facilitate efficient data warehousing, while Databricks will enable advanced analytics. The ideal candidate will have experience in MLOps to integrate machine learning models for predictive analytics, ensuring the solution not only captures current trends but anticipates future ones. This project is critical for maintaining our competitive edge and requires implementation within 8-12 weeks.