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Data Engineering with Generative and Agentic AI on AWS: Building an AI-Augmented Data Practice for the Enterprise — Justin J. Leto — 2026

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Supercharge AWS data engineering with generative and agentic AI to build intelligent data platforms Develop a modern data strategy with AWS to prepare your organization for the generative AI revolution Apply generative and agentic AI to transform every stage of the data engineering lifecycle This is a preview of subscription content, log in via an institution to check access. About this book 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. Who this Book Is For: Data engineers, analysts, architects, and tech leaders seeking practical guidance on AWS data engineering and generative AI, with or without prior cloud experience

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Data Engineering
with Generative and
Agentic AI on AWS
Building an AI-Augmented Data Practice
for the Enterprise

Justin J. Leto
Foreword by Shreyas Subramanian, PhD
Principal Data Scientist, AWS

, Data Engineering with
Generative and Agentic
AI on AWS
Building an AI-Augmented Data
Practice for the Enterprise




Justin J. Leto
Foreword by Shreyas Subramanian, PhD, Principal Data Scientist, AWS

,Data Engineering with Generative and Agentic AI on AWS: Building an
AI-Augmented Data Practice for the Enterprise
Justin J. Leto
Apress,
Long Island City, NY, USA

ISBN-13 (pbk): 979-8-8688-2198-1 ISBN-13 (electronic): 979-8-8688-2199-8
https://doi.org/10.1007/979-8-8688-2199-8
Copyright © 2026 by Justin J. Leto
This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the
material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation,
broadcasting, reproduction on microfilms or in any other physical way, and transmission or information
storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now
known or hereafter developed.
Trademarked names, logos, and images may appear in this book. Rather than use a trademark symbol with
every occurrence of a trademarked name, logo, or image we use the names, logos, and images only in an
editorial fashion and to the benefit of the trademark owner, with no intention of infringement of the
trademark.
The use in this publication of trade names, trademarks, service marks, and similar terms, even if they are not
identified as such, is not to be taken as an expression of opinion as to whether or not they are subject to
proprietary rights.
While the advice and information in this book are believed to be true and accurate at the date of publication,
neither the authors nor the editors nor the publisher can accept any legal responsibility for any errors or
omissions that may be made. The publisher makes no warranty, express or implied, with respect to the
material contained herein.
Managing Director, Apress Media LLC: Welmoed Spahr
Acquisitions Editor: Shaul Elson
Developmental Editor: Laura Berendson
Coordinating Editor: Gryffin Winkler
Cover designed by eStudioCalamar
Cover image by Freepik (www.freepik.com)
Distributed to the book trade worldwide by Springer Science+Business Media New York, 1 New York Plaza,
New York, NY 10004. Phone 1-800-SPRINGER, fax (201) 348-4505, e-mail , or
visit www.springeronline.com. Apress Media, LLC is a Delaware LLC and the sole member (owner) is
Springer Science + Business Media Finance Inc (SSBM Finance Inc). SSBM Finance Inc is a Delaware
corporation.
For information on translations, please e-mail ; for reprint,
paperback, or audio rights, please e-mail .
Apress titles may be purchased in bulk for academic, corporate, or promotional use. eBook versions and
licenses are also available for most titles. For more information, reference our Print and eBook Bulk Sales
web page at http://www.apress.com/bulk-sales.
Any source code or other supplementary material referenced by the author in this book is available to
readers on GitHub (https://github.com/Apress). For more detailed information, please visit https://www.
apress.com/gp/services/source-code.
If disposing of this product, please recycle the paper

, For Elsi and Atlas—believing it is possible lifts up the entire world.

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