Citation :

Lalmohan Behera, Vishnu Vardhan Reddy Chilukoori, 2025. "Automation in Data Engineering: Challenges and Opportunities in Building Smart Pipelines" ESP International Journal of Advancements in Computational Technology (ESP-IJACT)  Volume 2, Issue 2: 64-73.

Abstract :

The arrival of automation in data engineering has rewritten the way organizations manage Big Data processing and analytics. Automation-powered smart pipelines lend themselves to automated ingestion, transformation, and loading processes without much automation. However, embedding these pipelines into the real world brings the challenges of tool integration, data quality assurance, real-time processing and maintainability. This paper explores the thorny aspects of automating data engineering workflows, the problems it presents, and any possible solutions. Through a running example of data connectivity, the study identifies critical technologies and strategies, such as orchestration tools, machine learning-driven data quality checks, and the automated schema evolution that makes resilient pipelines possible. The paper also examines how cloud-native platforms and infrastructure as code play into enabling automated systems to be deployed and maintained optimally. Examples of real industrial applications, with their benefits and tradeoffs, are presented. With an awareness of the pipeline challenges and opportunities, data engineers and companies open up new efficiencies, innovations, and better decision-making. This paper gives actionable insights for practitioners who want to adopt or improve automation in their data engineering work.

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Keywords :

Data Engineering, Automation, Smart Pipelines, Data Quality, Scalability.