Real-Time Data Pipeline Optimization for Utility Resource Management

As a growing company in the Utilities industry, we face the challenge of managing and analyzing vast amounts of real-time data from electric, water, and gas meters. We seek to enhance our data pipeline architecture to support robust real-time analytics by leveraging advanced technologies such as Apache Kafka for event streaming and Apache Spark for real-time data processing. Our objective is to build a resilient data mesh that allows decentralized data ownership and faster data insights. The project involves designing and implementing a scalable and efficient data pipeline using Airflow for orchestration and dbt for data transformation. We aim to utilize Snowflake or BigQuery as our data warehouse solution for optimal performance and scalability. The ultimate goal is to enhance our operational efficiency, improve customer satisfaction, and ensure compliance with regulatory requirements. This project has a high level of urgency due to the pressing need for real-time data insights in decision-making and the growing demand for transparency from consumers and regulators. We require a skilled data engineer with experience in MLOps and data observability to ensure continuous monitoring and improvement of the data pipeline.