Data Modeller With Experience In Commercial Lending Domain

The Role

To support and lead the data modelling activities on cloud for Commercial lending data

Your responsibilities:

Key Responsibilities

1. Data Modelling
   • Develop and maintain conceptual, logical, and physical data models for Lending data domains.
   • Model Lending entities such as Facilities, Loans, Drawdowns, Collateral, Covenants, Parties, Exposure, and Repayments.
   • Ensure models support business requirements, regulatory needs, and data product consumption patterns.
   • Define data structures, relationships, keys, and data transformations required for implementation.
2. Requirement Analysis
   • Analyse and document business requirements from Lending SMEs, Credit Risk, Finance, and Regulatory Reporting.
   • Translate requirements into accurate and reusable data models.
3. Metadata & Documentation
   • Create and maintain data dictionaries, glossaries, and definitions for Lending data.
   • Document modelling decisions and data element definitions.
   • Ensure consistent naming conventions and modelling standards.
4. Data Quality & Lineage
   • Incorporate data quality rules into models (validations, reference data, master data requirements).
   • Support lineage documentation from upstream Lending systems to downstream applications.
   • Work with Data Quality and Governance teams to ensure traceability and compliance.
5. Cloud, Data Lake & Lakehouse (Modelling Only)
   • Design models suitable for cloud data platforms and lakehouse environments (Iceberg, Delta, Hudi).
   • Work with Data Engineers to ensure models are implemented effectively in S3 based or lakehouse environments.
   • Support schema evolution, partitioning definitions, and Medallion modelling (Bronze / Silver / Gold).
6. Regulatory & Reporting Support
   • Ensure models support regulatory obligations (IFRS9, PRA/EBA returns, BCBS 239).
   • Support lineage and traceability required for audit and compliance reviews.
7. Collaboration
   • Work closely with Lending SMEs, Data Engineers, DBAs, Data Quality, and Reporting teams.
   • Provide modelling inputs during solution design and delivery phases.

Your Profile

Essential skills/knowledge/experience:

1. A. Data Modelling Expertise
   • Strong hands on experience with conceptual, logical, and physical data modelling.
   • Proficiency with data modelling tools (ERwin, ER/Studio, PowerDesigner).
   • Experience maintaining glossaries, dictionaries, and model documentation.
2. B. Lending Domain Knowledge
   • Must understand key Lending concepts including:
   • Loan lifecycle (origination → booking → drawdown → servicing → closure)
   • Facilities, bilaterals, syndications, exposure, risk ratings
   • Interest accruals, schedules, restructuring
   • Security structures, collateral, covenants
   • Customer/party hierarchies
   • Experience with systems like LoanIQ, is highly advantageous.
3. C. Technical Skills
   • Strong SQL (DDL, DML, performance optimisation).
   • Scripting in PL/SQL, T SQL, Python or Shell (desirable).
   • Experience with relational and analytical databases (Oracle, SQL Server, PostgreSQL, Redshift, Snowflake).
   • Exposure to NoSQL stores (MongoDB, Cassandra) is beneficial.
4. D. Cloud & Lakehouse (Modelling focused)
   • Understanding of modern data lake/lakehouse modelling patterns.
   • Experience with AWS components: S3, Glue Catalog, Redshift, Athena.
   • Knowledge of Iceberg/Delta/Hudi modelling constraints (schema evolution, partitioning etc.).
5. E. Data Warehousing Concepts
   • Strong understanding of Kimball and/or Inmon methodologies.
   • Experience supporting ETL/ELT design with accurate models.
6. F. Governance, Controls & Regulations
   • Knowledge of BCBS 239 principles.
   • Understanding of regulatory and risk data needs (IFRS9, PRA/EBA, stress testing).
   • Ability to support audit/compliance documentation.
7. G. Professional & Analytical Skills
   • Excellent analytical and problem solving abilities.
   • Strong communication with both technical and business stakeholders.
   • Ability to translate complex processes into clear data structures.
   • High attention to detail.

Desirable skills/knowledge/experience:

• Self-driven with a strong desire to meet deadlines and to work accurately while keeping in mind compliance
• Innovation ideas, ability, courage and desire to suggest and develop novel approaches
• Good written and verbal communication in English

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