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Data Engineering with Generative and Agentic AI on AWS: Building an AI-Augmented Data Practice for the Enterprise Paperback - 2026
by Justin J. Leto
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Details
- Title Data Engineering with Generative and Agentic AI on AWS: Building an AI-Augmented Data Practice for the Enterprise
- Author Justin J. Leto
- Binding Paperback
- Condition New
- Pages 598
- Volumes 1
- Language ENG
- Publisher Apress
- Publication date 2026-05-13
- Illustrated Yes
- Features Illustrated
- Bookseller's Inventory # 53338557
- ISBN 9798868821981
- Weight 2.38 lbs (1.08 kg)
- Dimensions 10 x 7 x 1.27 in (25.40 x 17.78 x 3.23 cm)
- Category Computers - General Information
- Quantity available 2
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From the publisher
From the rear cover
Unlock the future of cloud data engineering with generative and agentic AI on AWS.
This hands-on guide shows you how to build intelligent, responsive data platforms using cutting-edge AI capabilities and modern AWS services.
Learn to design next-generation data architectures--from data lakes and data mesh to scalable pipelines and real-time analytics. Discover how generative AI and agentic automation are transforming every aspect of enterprise data work: ingesting unstructured data, enabling semantic search with Retrieval-Augmented Generation (RAG), building autonomous data agents, and using natural language interfaces to turn business questions into instant insights.
Author Justin J. Leto, PE, MBA, PMP, is a Principal Solutions Architect at AWS with over 20 years of experience in data engineering and AI. He doesn't just teach today's techniques--he prepares you for the future disruptions reshaping the field. His book is essential reading for current and aspiring data engineers, data analysts, data architects, engineering managers, CTOs, CDOs, and data-focused entrepreneurs looking to gain an edge over the competition.
What You Will Learn:
- Master the core principles and practices of data engineering to build a long, successful career in the field.
- Accelerate your impact using AWS cloud services for scalable, modern data solutions.
- Explore how the role of the modern data engineer is evolving to support generative and agentic AI use cases.
- Develop a modern data strategy by working backwards from business goals to gain buy-in from CxO-level leadership.
- Design and deploy modern data architectures--including data lakes, data mesh, and data marts--and understand when to use each.
- Apply generative and agentic AI to enhance every stage of the data engineering lifecycle.
- Evaluate emerging data and AI technologies using proven methodology to separate real value from hype.
- Prepare for the future of data engineering powered by autonomous agents that scale enterprise impact.
