Real-Time Data Pipeline Implementation for Enhanced Property Management Insights

As a fast-growing property management company, we are experiencing an increase in the volume and complexity of data collected from various sources, including tenant applications, maintenance requests, rental payments, and occupancy rates. Currently, our data integration and processing are done in batch mode, resulting in delays and missed opportunities for timely decision-making. We seek to transition to a real-time data pipeline that aggregates and processes data continuously. This project will involve designing a scalable architecture using Apache Kafka for event streaming, Apache Spark for processing, and Databricks for analytics. Airflow will be used for workflow management and dbt for transforming data in Snowflake or BigQuery, depending on the data's nature. The aim is to achieve real-time data processing and reporting, allowing property managers to react promptly to operational changes. The selected freelancer will work closely with our IT team to understand our existing systems, design the new architecture, implement the solution, and ensure data observability for ongoing monitoring. Success will be measured by the system's ability to deliver data insights significantly faster than our current setup, enhancing operational efficiency and competitive advantage.