VP Data Modeler

About the Team & Business Line:

Fund Administration is Citco’s core business, and our alternative asset and accounting service is one of the industry’s 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 Citco’s 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:

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.

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.