Position Overview
We are seeking a highly skilled Data Modeler to design and implement structural data schemas for our financial services clients. This role will translate complex business requirements and multi-source systems into robust data structures. The modeler will own the hands-on creation of normalized, dimensional, and unified information models- ensuring data integrity, optimized storage, and high-performance query execution across enterprise data platforms.
Key Responsibilities
Data Model Creation: Design and develop end-to-end Conceptual, Logical, and Physical Data Models (PDM) to map complex business processes into structured data entities.
Unified Model Mapping: Construct Common Information Models (CIM) and standardized target schemas to unify disparate, siloed source system feeds into single-source-of-truth data products.
Schema Design Optimization: Implement scalable data warehouse and data lake schemas, utilizing Industry-standard methodologies such as Dimensional Modeling (Star/Snowflake schemas), Data Vault, and Third Normal Form (3NF).
Required Skills & Experience
Experience 8 - 10 years
Financial Services Domain Expertise: Strong data modeling experience across banking and financial services domains (such as Treasury, Wealth Management, Corporate Banking, or Risk & Compliance). Proven track record of modeling financial transactions, party/customer mastering, and complex balance sheet or GL data structures.
Technical Stack & Tool Proficiency: Expert-level proficiency with enterprise data modeling tools like Erwin Data Modeler. Solid understanding of modeling for modern cloud data platforms, including Azure Databricks, and big data formats (such as Delta Lake or Apache Iceberg).
SQL Mastery & Profiling: Advanced SQL capabilities with a deep understanding of relational databases and data profiling techniques to analyze source data quality, structural patterns, and volume distributions.
