Real-time Data Pipeline Implementation for Enhanced Cleaning & Maintenance Operations

Our scale-up company in the Cleaning & Maintenance industry is poised to revolutionize the way we manage operations by harnessing the power of real-time data analytics. Currently, our IoT-enabled cleaning devices generate vast amounts of data, but the lack of an efficient data pipeline limits our ability to extract actionable insights. We aim to implement a real-time data pipeline using Apache Kafka for event streaming, Spark for processing, and Snowflake or BigQuery for storage and analysis. The project will also involve using Airflow for workflow management and dbt for data transformation, ultimately creating a scalable data mesh architecture. This initiative will empower us to monitor equipment status, predict maintenance needs, and optimize resource allocation with precision. The ideal candidate will have experience in real-time analytics, MLOps, and data observability, ensuring that the pipeline is not only effective but also sustainable. The successful completion of this project will enable us to enhance operational efficiency significantly, reduce downtime, and increase customer satisfaction.