Senior Data Modeler

Job Description Role Overview We are looking for an experienced Data Modeler / Senior Data Modeler to support the expansion of an established enterprise Finance Data Platform within a leading global bank. The existing platform has been implemented for the Markets business, with established data models, data management standards, governance frameworks, and processing capabilities. The next phase will focus on onboarding additional business areas, including Corporate Banking, Wealth Management, Private Banking, and other banking businesses, onto the common Finance Data Platform. The role will focus on understanding the data structures, products, processes, and Finance requirements of these businesses and extending, adapting, and harmonising the existing enterprise data model to support them. Key Responsibilities 1. Analyse and extend the existing Finance data model developed for the Markets business to support additional business areas, while maximising reuse of existing entities, attributes, structures, and design patterns. 2. Design and maintain conceptual, logical, and physical data models covering products, transactions, positions, balances, customers, accounts, legal entities, cash flows, valuations, accounting attributes, and reporting data. 3. Understand the data landscape and product structures of newly onboarded businesses, including Corporate Banking, Wealth Management, Private Banking, Lending, Deposits, Treasury, and Investment Products, and identify common and business-specific data requirements. 4. Drive data harmonisation and standardisation across business areas by defining common business concepts, enterprise entities, attributes, hierarchies, taxonomies, reference data, and consistent data definitions. 5. Define source-to-target mappings, transformation rules, derivations, enrichment logic, and model extensions required to integrate new business data into the existing Finance Data Platform. 6. Perform detailed data analysis and profiling using advanced SQL to validate data structures, relationships, cardinality, business rules, data quality, and assumptions underpinning the target data model. 7. Ensure the data model supports downstream Finance requirements, including Financial Accounting, Product Control, FP&A, Financial Reporting, Regulatory Reporting, Management Reporting, reconciliation, and analytics. 8. Work with Finance SMEs, Data Analysts, Data Architects, Data Engineers, Governance, and Technology teams to ensure scalable implementation, appropriate metadata and lineage, adherence to modelling standards, and alignment with the broader Finance data architecture. Required Skills and Competencies 1. Strong enterprise data modelling experience, including conceptual, logical, and physical data modelling, with proven experience extending or harmonising existing enterprise data models. 2. Strong banking and Finance domain knowledge, with experience across multiple business areas such as Markets, Corporate Banking, Commercial Banking, Wealth Management, Private Banking, Lending, Deposits, or Treasury. 3. Advanced hands-on SQL skills for data profiling, structural and relationship analysis, reconciliation, source-to-target validation, exception analysis, and investigation of large and complex datasets. 4. Strong end-to-end data management experience, covering data sourcing, profiling, harmonisation, modelling, transformation, validation, reconciliation, data quality, metadata, lineage, governance, and reporting. 5. Experience working with large-scale modern data platforms and data management tools, including technologies such as Databricks, Snowflake, Hadoop, Spark, data lakes or lakehouses, and modelling or governance tools such as ERwin, PowerDesigner, Informatica, Collibra, or equivalent. 6. Strong analytical, consulting, stakeholder management, and communication skills, with the ability to engage Finance, Business, Architecture, Engineering, Governance, and Technology stakeholders and translate complex business requirements into scalable enterprise data models. CRISIL