Real-Time Data Engineering Pipeline for Enhanced Logistics Efficiency

Our enterprise logistics company seeks a skilled data engineer to design and implement a robust real-time data pipeline. This solution will integrate Apache Kafka for event streaming and Spark for real-time data processing, ensuring efficient data flow from various sources. Utilizing Airflow for workflow orchestration and dbt for data transformation, the pipeline will feed into Snowflake or BigQuery for advanced analytics and insights. The project will also incorporate data mesh principles and MLOps practices to enhance data accessibility and operationalize machine learning models for predictive logistics. The goal is to create a centralized data platform that provides real-time visibility into our logistics operations, enabling faster decision-making, improved inventory management, and enhanced customer satisfaction. This initiative is critical to maintaining our competitive edge in an increasingly data-driven industry.