Data Modeler with a strong Investment Banking and Financial Services
Posted 3 days ago by Delviom LLC
Negotiable
Undetermined
Remote
Remote
Summary: We are seeking an experienced Data Modeler with expertise in Investment Banking and Financial Services to design, develop, and maintain scalable data models. The role involves collaborating with business stakeholders to understand data requirements and ensuring compliance with regulatory standards. The ideal candidate will also optimize data models for performance and support data integration from various sources.
Key Responsibilities:
- Design and develop conceptual, logical, and physical data models for investment banking and financial analytics platforms
- Work closely with business stakeholders (front office, risk, compliance, finance) to understand data requirements
- Translate complex financial data into structured models for reporting and analytics
- Develop and maintain data dictionaries, metadata, and lineage documentation
- Ensure data models support regulatory reporting and compliance requirements
- Collaborate with data engineers and architects to implement models in data warehouses / lakes
- Optimize data models for performance, scalability, and data integrity
- Support integration of data from multiple sources including trading systems, market data providers, and internal platforms
- Participate in data governance and quality initiatives
Key Skills:
- Strong experience in data modeling (ER modeling, dimensional modeling star/snowflake schemas)
- Proven experience in Investment Banking / Capital Markets / Financial Services domain
- Deep understanding of financial instruments such as equities, fixed income, derivatives, and structured products
- Hands-on experience with data modeling tools (e.g., ERwin, ER/Studio, PowerDesigner)
- Strong SQL skills and familiarity with relational databases (Oracle, SQL Server, PostgreSQL)
- Experience working with data warehouses and big data platforms (e.g., Snowflake, Hadoop, Databricks)
- Knowledge of financial data standards and regulatory frameworks
- Understanding of data governance, data quality, and lineage concepts
Salary (Rate): undetermined
City: undetermined
Country: undetermined
Working Arrangements: remote
IR35 Status: undetermined
Seniority Level: undetermined
Industry: Other
We are seeking an experienced Data Modeler with a strong background in Investment Banking and Financial Services. The ideal candidate will design, develop, and maintain scalable data models that support analytics, reporting, and regulatory requirements across investment banking
Key Responsibilities
Design and develop conceptual, logical, and physical data models for investment banking and financial analytics platforms
Work closely with business stakeholders (front office, risk, compliance, finance) to understand data requirements
Translate complex financial data into structured models for reporting and analytics
Develop and maintain data dictionaries, metadata, and lineage documentation
Ensure data models support regulatory reporting and compliance requirements
Collaborate with data engineers and architects to implement models in data warehouses / lakes
Optimize data models for performance, scalability, and data integrity
Support integration of data from multiple sources including trading systems, market data providers, and internal platforms
Participate in data governance and quality initiatives
Required Skills & Qualifications
Strong experience in data modeling (ER modeling, dimensional modeling star/snowflake schemas)
Proven experience in Investment Banking / Capital Markets / Financial Services domain
Deep understanding of financial instruments such as equities, fixed income, derivatives, and structured products
Hands-on experience with data modeling tools (e.g., ERwin, ER/Studio, PowerDesigner)
Strong SQL skills and familiarity with relational databases (Oracle, SQL Server, PostgreSQL)
Experience working with data warehouses and big data platforms (e.g., Snowflake, Hadoop, Databricks)
Knowledge of financial data standards and regulatory frameworks
Understanding of data governance, data quality, and lineage concepts