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 view 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 who specializes in finance not only has specific data engineering knowledge, but also a good understanding of financial domain-specific problems, approaches, data ecosystem, data providers, data formats, technological constraints, identifiers, entities, regulatory requirements, and governance.

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

You'll learn:

• The data engineering landscape in the financial sector
• Specific problems encountered in financial data engineering
• 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 and cloud technologies