Real-Time Data Pipeline Enhancement for Customs & Immigration Analytics

As a scale-up company in the Customs & Immigration sector, we are seeking to enhance our data engineering infrastructure to support real-time analytics and improve operational efficiency. The project involves designing and implementing a robust data pipeline that leverages Apache Kafka for event streaming and Spark for real-time data processing. By integrating Snowflake and BigQuery for data warehousing, and utilizing Airflow for orchestration, we aim to create a seamless data flow that provides accurate insights when they matter most. Key objectives include reducing data latency, increasing data reliability through MLOps and data observability techniques, and ensuring scalability to handle increasing data volumes. The successful completion of this project will enable our team to make informed, data-driven decisions that enhance the effectiveness of customs operations, improve compliance, and boost overall service efficiency.