Data Engineer - Regulatory Reporting (IFRS9, Basel)

Overview

We are seeking a skilled Data Engineer specialized in regulatory reporting focused on IFRS9 and Basel regulations. The role demands designing and maintaining robust data pipelines and supporting credit risk data management, model implementation, quality assurance, system integration, and reporting automation within a financial services context.

Key Responsibilities

• Develop and sustain scalable ETL pipelines leveraging SQL, Python, and SAS to manage large datasets.
• Manage datasets related to default identification, post-default activities, recoveries, and exposure assessment.
• Apply incremental and full data load methods that prevent data duplication and leakage.
• Optimize SQL queries for distributed and big data platforms.
• Integrate complex data from banking systems, collection departments, GSAM, and external sources.
• Translate IFRS9 accounting methodology into technical data pipelines supporting PD, LGD, and EAD model datasets.
• Implement staging processes (Stage 1/2/3), and apply default and curing criteria for accurate credit risk data preparation.
• Handle calculations related to recoveries, write-offs, restructures, and exposure.
• Provide model-ready datasets for deployment and assist in feature engineering, segmentation, and backtesting processes.
• Perform detailed reconciliations between developed and reference data outputs, identifying discrepancies.
• Establish data quality frameworks emphasizing completeness, accuracy, and consistency, alongside root cause analyses on data inaccuracies.
• Maintain comprehensive data lineage and ensure traceability throughout data processes.
• Collaborate with IT teams for system integration, model deployment, risk system upgrades, and migrations.
• Conduct testing to validate data migration and model precision.
• Automate the generation of regulatory and internal reports, preparing datasets compatible with dashboards and submissions.
• Support usage of BI reporting tools such as Power BI and SAP BusinessObjects.

Technical Environment and Expertise

• Proficiency with SQL platforms including Impala, Hive, and Oracle.
• Hands-on experience with Python and SAS for data processing.
• Familiar with Cloudera CDP for big data management.
• Expertise in regulatory frameworks IFRS9, Basel II/III.
• Knowledge of credit risk parameters such as Probability of Default (PD), Loss Given Default (LGD), and Exposure at Default (EAD).