Real-Time Data Pipeline Enhancement for Personalized Service Optimization

As a fast-growing startup in the Personal Services industry, we are committed to delivering exceptional value to our clients by tailoring services to individual preferences. To achieve this, we need to enhance our existing data infrastructure to support real-time data ingestion, processing, and analytics. The project involves building a robust data pipeline using technologies such as Apache Kafka for event streaming, Spark for fast data processing, and Airflow for orchestrating data workflows. The objective is to enable our service platform to analyze user behavior and preferences in real-time, allowing for dynamic service recommendations and improved user experiences. Additionally, we aim to implement data observability practices to ensure data accuracy and reliability. The ideal candidate will have experience with dbt for data transformation and Snowflake or BigQuery for data warehousing. This project is crucial for maintaining competitive advantage and ensuring customer satisfaction.