Data engineer - regulatory reporting ( IFRS9, Basel

Key Responsibilities:

1. ETL & Risk Data Engineering

• Design, develop and maintain scalable ETL pipelines using SQL, Python, and SAS
• Support datasets for default identification, post-default events, recovery, and exposure
• Implement incremental and full-load strategies ensuring no duplication or leakage
• Optimize SQL for large-scale distributed processing environments
• Integrate data from core banking, collections, GSAM, and external sources
  2. IFRS9 & Credit Risk Data Management
• Translating IFRS9 methodology into technical data pipelines
• Support PD, LGD, EAD model data preparation
• Implement staging (Stage 1/2/3), default, and curing logic
• Handle recoveries, write-offs, restructures, and exposure calculations
  3. Model Implementation & Validation Support
• Provision model-ready datasets for deployment
• Support feature engineering, segmentation, and backtesting datasets
• Perform reconciliation with developed/reference outputs and identify mismatches
  4. Data Quality & Governance
• Develop DQ frameworks covering completeness, accuracy, and consistency
• Perform root cause analysis on data issues
• Ensure full data lineage and traceability
  5. Risk Technology & System Integration
• Collaborate with IT for system integration and model deployment
• Support risk system migration and upgrades
• Perform testing for data migration and model accuracy
  6. Automation & Reporting
• Automate regulatory and internal reporting processes
• Prepare datasets for dashboards and regulatory submissions
• Support reporting tools such as Power BI and Business Objects Preferred Tools & Technologies: SQL (Impala, Hive, Oracle), Python, SAS, Cloudera CDP, Power BI, SAP BO Core Domain Expertise: IFRS9, Basel II/III, PD/LGD/EAD modelling, credit risk data lifecycle
  
  Skills:
  
  data,etl,reporting