Today, investment in financial technology and digital transformation is reshaping the financial landscape and generating many opportunities. Too often, however, engineers and professionals in financial institutions lack a practical and comprehensive understanding of the concepts, problems, techniques, and technologies necessary to build a modern, reliable, and scalable financial data infrastructure. This is where financial data engineering is needed.

A data engineer developing a data infrastructure for a financial product possesses not only technical data engineering skills but also a solid understanding of financial domain-specific challenges, methodologies, data ecosystems, providers, formats, technological constraints, identifiers, entities, standards, regulatory requirements, and governance.

This book offers a comprehensive, practical, domain-driven approach to financial data engineering, featuring real-world use cases, industry practices, and hands-on projects.

You'll learn:

• The data engineering landscape in the financial sector
• Specific problems encountered in financial data engineering
• The structure, players, and particularities of the financial data domain
• Approaches to designing financial data identification and entity systems
• Financial data governance frameworks, concepts, and best practices
• The financial data engineering lifecycle from ingestion to production
• The varieties and main characteristics of financial data workflows
• How to build financial data pipelines using open source tools and APIs

Tamer Khraisha is a senior software and data developer, as well as a scientific author, with over a decade of experience in both industry and research. Tamer's experience combines a solid background in financial markets with substantial expertise in software engineering. He did his undergraduate studies in finance and economics and earned a PhD in network science. Tamer's research interests are focused on financial markets, data, and technology. During his professional career, Tamer has worked with various FinTech startups, where he designed and built data-driven cloud platforms for financial research, artificial intelligence, and asset management, as well as international payment systems.