Data Modeler - Hybrid

Data Modeler Key Responsibilities • Design scalable data models optimized for Snowflake's cloud-native architecture, including use of virtual warehouses, clustering keys, and materialized views. • Develop conceptual, logical, and physical data models that align with financial regulatory requirements (e.g., Basel III, SOX, GDPR). • Collaborate with data engineers and architects to implement models that support real-time analytics, fraud detection, and risk management. • Ensure data quality and consistency across diverse financial systems such as trading platforms, customer onboarding, and compliance tools. • Integrate structured and semi-structured data (e.g., JSON, XML) using Snowflake's native capabilities to support complex financial reporting. • Document data lineage and metadata to support auditability and transparency for internal and external stakeholders. • Optimize data storage and query performance using Snowflake-specific features like automatic clustering and query profiling. • Support data governance initiatives by aligning models with enterprise data catalogs, stewardship policies, and access controls. • Collaborate with business analysts and compliance teams to translate financial reporting needs into robust data structures. • Continuously refine models based on evolving financial products, market conditions, and regulatory changes.

Technical Skills • Proficiency in designing conceptual, logical, and physical data models. • Strong SQL skills and experience with Snowflake-specific features (e.g., Snowpipe, Streams, Tasks, Time Travel). • Familiarity with data modeling tools (e.g., ER/Studio, ERwin, dbt, or similar). • Understanding of data warehousing principles, dimensional modeling, and normalization techniques. • Experience integrating structured and semi-structured data (e.g., JSON, XML) in Snowflake.