Real-Time Data Pipeline Optimization for Enhanced Property Insights

As a growing player in the Residential Real Estate industry, our company aims to gain a competitive edge by providing clients and agents with real-time property data and analytics. We are looking to optimize our data infrastructure by implementing a state-of-the-art data pipeline. The project involves architecting a system using technologies like Apache Kafka for event streaming, Spark for real-time analytics, and Airflow for workflow management. Additionally, Snowflake or BigQuery will be employed as our cloud data warehouse solutions, while dbt will serve for data transformation and modeling. The goal is to provide our sales team, management, and clients with timely and accurate information, enabling better decision-making and a superior customer experience. The successful execution of this project will establish a scalable data mesh architecture, facilitating data observability and governance across the organization. The initiative is scheduled for completion within 12-16 weeks, with a focus on integrating MLOps practices to streamline machine learning model deployment.