Data Modeller With Experience In Commercial Lending Domain

Avance Consulting; England; On-site; GBP 70,000 - 110,000; Full time

Job summary

Avance Consulting in the United Kingdom seeks a Senior Data Modeller to lead data modelling on cloud for Commercial lending data. You will design conceptual, logical, and physical models for lending entities and ensure alignment with business and regulatory needs.

Work with Lending SMEs, Data Engineers, and Governance teams to deliver scalable lakehouse-ready models on AWS, with emphasis on data quality, lineage, and documentation. Strong SQL and experience with lending ecosystems are required.

Qualifications

• Hands-on data modelling across conceptual, logical and physical layers.
• Experience with lending data concepts and risk/regulatory needs.
• Proficiency in SQL and data transformation concepts.

Responsibilities

• Lead data modelling for lending data domains and cloud platforms.
• Develop models for Facilities, Loans, Collateral, Covenants, Parties, Exposure and Repayments.
• Ensure alignment with business, regulatory and data product needs.
• Create data dictionaries and maintain modelling standards.

Skills

Data modelling

Cloud modelling

Stakeholder comms

Lending domain knowledge

SQL proficiency

Regulatory concepts

Tools

ERwin

ER/Studio

PowerDesigner

Snowflake

Job description

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