Data Modeler

Overview:

Data Modeler

- Design scalable data models optimized for Snowflakes 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 Snowflakes 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.

Qualifications Education Experience

- Bachelors degree in Computer Science, Information Systems, Data Science, or a related field (Masters preferred).

- 5 years of experience in data modeling, with at least 2 years working with Snowflake in a production environment.

- Prior experience in the financial services industry, with familiarity in domains like risk, compliance, trading, or customer analytics.

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., ERStudio, 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.

- Domain Knowledge Knowledge of financial data structures and regulatory requirements (e.g., SOX, Basel III, GDPR).

- Experience working with data governance, metadata management, and data quality frameworks.

- Soft Skills Strong collaboration and communication skills to work with cross-functional teams including data engineers, analysts, and compliance officers.

- Ability to translate business requirements into scalable and efficient data models.

- Detail-oriented with a focus on data accuracy, consistency, and performance.