Real-Time Data Pipeline Optimization for Autonomous Vehicle Fleet Management

Our enterprise is seeking a data engineering expert to design and implement a real-time data pipeline aimed at optimizing our autonomous vehicle fleet management. The project's objective is to harness the power of real-time analytics, data mesh architecture, and MLOps to improve operational efficiency and decision-making processes. The scope includes setting up an event streaming system using Apache Kafka, implementing data processing with Spark, orchestrating workflows with Airflow, and integrating data observability solutions. The pipeline will need to handle vast amounts of data generated by the fleet, ensuring low-latency insights and high data quality. Additionally, the project will incorporate dbt for data transformations and Snowflake or BigQuery for scalable, secure storage. A significant aspect will be the integration with existing Databricks platforms to facilitate machine learning efforts. This initiative is crucial to maintaining our competitive edge in the highly dynamic autonomous vehicles market, and it is expected to set new benchmarks in data handling efficiency.