Generative AI is transforming data engineering workflows by automating labor-intensive tasks like schema generation, pipeline debugging, and anomaly detection. Tools leveraging LLMs (Large Language Models) are now capable of understanding natural language queries, enabling non-technical stakeholders to define pipeline requirements without extensive technical involvement.
Moreover, AI is being embedded into ETL (Extract, Transform, Load) pipelines for predictive data transformations and optimization. This has significantly reduced engineering time, enabling teams to focus on strategic initiatives like building robust data architectures and ensuring compliance with growing data privacy regulations.
