Real-Time Data Pipeline Optimization for Maritime Fleet Management

As a rapidly growing company in the Maritime & Shipping industry, we are committed to leveraging data-driven insights to stay competitive. Our current data pipeline struggles with latency issues and lacks the scalability needed to handle our expanding fleet's data volume. We need an expert data engineer to redesign our real-time data pipeline, ensuring it is robust, scalable, and capable of delivering real-time analytics. The project involves integrating Apache Kafka for efficient event streaming, utilizing Spark for real-time analytics processing, and setting up data observability with Airflow and dbt to ensure data quality and lineage tracking. Additionally, the solution will involve deploying the pipeline on flexible cloud data platforms like Snowflake or BigQuery, with a potential exploration of Databricks for advanced analytics and machine learning operations (MLOps). This project is crucial for our operations to maintain safety standards, optimize routes, and reduce fuel consumption. A successful implementation will provide our operations team with the ability to make informed decisions in real-time, translating into significant cost savings and improved fleet utilization.