Real-Time Data Pipeline for Enhanced Investment Analytics

As a leading enterprise in the Investment & Securities industry, we are committed to delivering data-driven insights that enhance our investment strategies. The current challenge lies in the delays and inaccuracies in data processing that hinder our ability to provide real-time analytics and insights to our analysts. We are looking to develop a comprehensive data pipeline that integrates Apache Kafka for event streaming, uses Spark for large-scale data processing, Airflow for orchestrating complex workflows, and utilizes dbt for data transformation. The pipeline should feed into Snowflake or BigQuery for storage and analysis, with an emphasis on ensuring data quality through MLOps and observability frameworks. This project aims to build a scalable and manageable data mesh architecture that provides seamless data access across the organization, enabling analysts to quickly adapt to market changes and make timely investment decisions. The successful completion of this project will position us as a leader in data-driven investment decisions, ensuring quick response times and accurate analytics.