[ Updated for 2026] : [This article was originally written in 2022 and has been revised to reflect current Data Engineering and AI interview trends.] In recent years, the exponential growth of data—driven by cloud adoption, digital products, IoT, and AI systems has made data a core business asset for almost every organization. As a result, companies across industries are heavily investing in data platforms to enable analytics, real-time insights, and AI-driven decision-making. This shift has significantly increased demand for Data Engineering roles, and Data Engineers continue to be among the most in-demand and strategically critical profiles in the IT industry. By 2026, the role of a Data Engineer has evolved beyond traditional ETL development. Organizations now expect Data Engineers to design scalable, reliable, and AI-ready data platforms that can support analytics, machine learning, and Generative AI use cases. Modern data teams rely on Data Engineers to build robust ingestion p...
Data Engineering interview preparation with practical insights on SQL, coding, data pipelines, cloud platforms (GCP, AWS), Snowflake, dbt, Fivetran, and AI-driven data systems. This Blog is based on real-world and personal experiences.