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, PhD, is a senior data engineer and scientific author with more than a decade of experience in the financial sector.