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

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
  

• 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.
  

• 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.
  

• Experience working within large enterprise banking environments.
  

• Exposure to enterprise architecture review processes.
  

• Strong stakeholder collaboration and documentation skills.