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 Skills: data,etl,reporting