Real-time Data Pipeline Optimization for Enhanced Property Insights

In the competitive landscape of real estate investment, having access to precise and timely property data is critical. Our PropTech SME specializes in providing comprehensive property insights to real estate investors. Currently, our data infrastructure struggles with latency issues and lacks the ability to deliver real-time analytics, which limits our clients' decision-making capabilities. We are seeking a skilled data engineering team to design and implement a robust data pipeline that can handle real-time data ingestion and processing. The project's goal is to utilize technologies such as Apache Kafka for event streaming, Spark for in-memory processing, and Snowflake for data warehousing to create a data mesh architecture. This setup will ensure data observability and MLOps capabilities are integrated for ongoing data quality and model updates. The successful implementation will result in enhanced data accuracy and insight depth, enabling our clients to maintain a competitive advantage in the real estate market.