Quant Data Engineer Interview Questions and Key Topics
As firms increasingly rely on data-driven strategies, the expectations for Quant Data Engineers have expanded far beyond traditional data engineering. They must be fluent in data warehousing, scalable analytics, performance tuning, and the latest open-source technologies, while also understanding the nuances of financial data.
Modern architectures have evolved from traditional data warehouses to lakehouses, combining the flexibility of data lakes with the reliability and performance of warehouses. Let’s break down the essential components, technologies, and their practical applications.
Columnar formats like Parquet and ORC are designed for analytical workloads, where operations often scan only a few columns across many rows. Understanding their benefits is essential for optimizing storage and query performance.
