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 BusinessObjects 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