Artificial Intelligence is fundamentally transforming the discipline of data engineering. This paper examines how AI is reshaping core data engineering functions including relational and cloud database management, data warehousing, enterprise analytics, digital analytics platforms such as Adobe Analytics, and cloud-native platforms such as Snowflake. Drawing on current industry practices and emerging platform capabilities, this paper analyzes the impact of AI on pipeline development, data quality management, automated metadata governance, and real-time analytics. This paper further discusses how the role of the data engineer is evolving from manual code writing to strategic architecture and AI-assisted orchestration. The paper also addresses key challenges including data privacy in regulated financial environments, skill evolution requirements, and the governance of AI-generated outputs. Paper findings indicate that organizations which invest in AI-ready data infrastructure, establish strong governance frameworks, and upskill their engineering teams will gain significant competitive advantages in the next decade.
Sowmya Yattapu (Thu,) studied this question.