Data Engineering Fundamentals

The Data Engineering Fundamentals interview evaluates your ability to design and optimize scalable data systems that enable analytics, reporting, and machine learning. This mock interview simulates real-world data engineering challenges across data ingestion, SQL querying, schema design, warehousing, and big data optimization.

You’ll demonstrate practical knowledge of how raw data flows through modern architectures — from ingestion and transformation to storage and consumption. The interview emphasizes designing efficient ETL pipelines, writing performant SQL queries, and implementing schemas optimized for analytics workloads. It also assesses your understanding of distributed systems, data partitioning, and pipeline reliability, preparing you for production-scale scenarios.

By completing this interview, you’ll gain hands-on experience in end-to-end data engineering workflows, improve your ability to reason about trade-offs in design and scalability, and strengthen your readiness for technical interviews at top data-driven companies.

Goals of the Interview:

1. Explain the data engineering lifecycle and objectives.
2. Design reliable data ingestion and transformation pipelines.
3. Write optimized SQL queries for large datasets.
4. Create efficient schema and data warehouse designs.
5. Optimize systems using big data frameworks and tools.