Real-Time Data Pipeline Implementation for Event Insights Optimization

Our startup is aiming to revolutionize the catering and event planning industry by leveraging real-time data analytics to enhance operational efficiency and customer satisfaction. Currently, our data is siloed across multiple platforms, resulting in delayed insights and suboptimal decision-making. We are seeking an experienced data engineer to design and implement a real-time data pipeline using cutting-edge technologies like Apache Kafka for event streaming, Apache Spark for real-time processing, and Snowflake or BigQuery for data warehousing. The project will focus on integrating data from sales, customer feedback, and operational systems to provide immediate insights into event performance and customer preferences. Additionally, using tools like Airflow and dbt, we aim to automate data workflows and ensure data transformation processes are seamless. This implementation will enable our team to make data-driven decisions quickly, improve event outcomes, and enhance customer experiences. The project is high priority with a timeline of 4-6 weeks, aiming to establish a foundational infrastructure that supports future scalability and data-driven innovation.