VP Data Modeler
VP Data Modeler
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Job Description
About the Team & Business Line:
Fund Administration is Citcos core business and our alternative asset and accounting service is one of the industrys most respected. Our continuous investment in learning and technology solutions means our people are equipped to deliver a seamless client experience.
Your Role:
We are looking for a Vice President Data Modeler to define the core structured datasets that power Citcos internal & external data marketplace. This person will work with cutting-edge financial data technologies creating the bridge between raw data and actionable insights while ensuring data is optimized for analytics reporting and API-based access.
Responsibilities
Responsibilities:
Data Modelling & Structuring (DataBricks Medalion Architecture)
Design aggregated structured datasets to ensure Gold Layer data is business ready.
Define fund data relationships across multiple sources.
Optimize data models for performance governance and reporting.
Create SQL-based views and transformations to standardize data models.
Work with the internal data engineering team to ensure transformations align with consumer requirements.
Partner with VP Data Analyst & BI Analysts to validate data structures and support analytics.
Collaborate with the product & API teams to ensure Gold Layer datasets are accessible for internal & external users.
Ensure efficient query performance (partitioning indexing data structures).
Work with governance teams to define dataset permissions & access rules.
About You:
6-10 years of experience as a Data Modeler Data Architect or Data Engineer in fund administration asset management or financial services.
Hands-on experience designing structured financial datasets for analytics & reporting.
Experience working with cloud-based data platforms & SQL-based data modelling.
Experience optimizing financial data for query performance & analytics.
Ability to translate business needs into structured data models.
Familiarity with governance & compliance frameworks for financial data.
Experience working cross-functionally with finance compliance risk & product teams.
Qualifications
Technical Skills
Advanced SQL (Databricks Snowflake PostgreSQL or similar) Ability to build complex data models.
Data Modelling (Star Schema Normalization Dimensional Modelling) Strong expertise in structuring datasets.
ETL & Data Transformation (dbt SQL Views Dataflows or similar) Experience optimizing data for Gold Layer reporting.
Python (Pandas PySpark or NumPy Optional) Nice-to-have for advanced data manipulation.
Experience optimizing financial data for query performance & analytics.
Ability to translate business needs into structured data models.
Required Experience:
Exec
Employment Type
Full-Time
