Source: https://www.udemy.com/course/data-engineering-for-risk-finance-sql-aws-azure/What you’ll learn
- Design end-to-end data engineering pipelines for financial risk use cases (credit risk, IFRS 9, ECL, regulatory reporting).
- Build production-ready SQL data models for PD, LGD, EAD, exposure, and time-series macroeconomic data.
- Implement cloud-based data pipelines on AWS and Azure, including ingestion, transformation, and orchestration.
- Engineer risk-grade data layers (raw, staging, curated, analytics) aligned to banking governance and audit expectations.
- Integrate Python, SQL, and cloud services to automate data validation, reconciliation, and controls.
- Apply data quality frameworks used in regulated financial institutions (completeness, accuracy, timeliness, lineage).
- Prepare model-ready datasets for credit risk, stress testing, and IFRS 9 scenario analysis.
- Translate regulatory and business requirements into scalable data architectures for risk and finance teams.
Requirements
- Basic understanding of SQL (SELECT, JOIN, GROUP BY)
- Familiarity with Python or any programming language is helpful
- General awareness of finance, banking, or risk concepts (not required)
Download Links
Password: cms.ddpanda.org
Host: FreeDL
