Publisher's Synopsis
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
