Real-Time Data Pipeline for Predictive Delivery Optimization

As a growing player in the trucking and delivery industry, our company is focused on leveraging data to enhance our delivery operations. We aim to implement a real-time data pipeline capable of ingesting and processing data from GPS, traffic updates, weather forecasts, and internal logistics systems. The project involves designing and developing a robust data architecture using Apache Kafka for event streaming, Spark for scalable data processing, and Airflow for orchestrating data workflows. The processed data will be stored in Snowflake and made available for analysis in BigQuery. Predictive models will be developed using Databricks to optimize delivery schedules and routes. The goal is to achieve significant reductions in delivery times, fuel costs, and improve customer satisfaction. We expect the candidate to have strong experience in MLOps, data observability, and a clear understanding of data mesh concepts.