Lead / Senior Data Modeler – Capital Markets & U.S. Regulatory Reporting

Role Description Seeking an experienced Data Modeler with strong expertise in Capital Markets, Banking, and U.S. Regulatory Reporting domains. The candidate will be responsible for designing and maintaining enterprise data models supporting trading, risk, finance, compliance, and regulatory reporting initiatives across capital markets platforms.

The role requires a deep understanding of financial products, trade lifecycle processes, regulatory data requirements, and modern cloud-based data architectures. Experience Required: 10+ Years Keywords: Data Concepts, Data Modelling Key Responsibilities Data Modeling: Design and develop conceptual, logical, and physical data models for enterprise data platforms.

Integration: Create canonical data models supporting cross-functional integration across Front Office, Risk, Finance, Operations, and Compliance domains. Analysis: Analyze and model enterprise data structures and relationships. Governance & Documentation: Develop and maintain metadata, data lineage, data dictionaries, and governance documentation.

Collaboration: Work closely with ETL/ELT, Snowflake, Databricks, and cloud engineering teams for implementation alignment. Quality Assurance: Ensure data quality, consistency, auditability, and reconciliation across platforms. Review Processes: Participate in data governance and enterprise architecture review processes.

Optimization: Optimize data structures for analytics, reporting, and downstream consumption. Essential Skills Domain Knowledge: Strong expertise in Capital Markets, Banking, and U.S. Regulatory Reporting. Platform Design: Experience designing enterprise data models for trading, risk, finance, compliance, and regulatory reporting platforms.

Financial & Cloud Literacy: Strong understanding of financial products, trade lifecycle processes, regulatory data requirements, and cloud-based data architectures. Technical Execution: Hands-on experience with ETL/ELT processes, Snowflake, Databricks, and enterprise data platforms. Data Governance: Strong knowledge of data governance, metadata management, data lineage, data quality, and reconciliation.

Performance: Experience optimizing data models for analytics and reporting. Desirable Skills Experience working within large enterprise banking environments. Exposure to enterprise architecture review processes. Strong stakeholder collaboration and documentation skills.