Data Modeler

Key Responsibilities

• Data Modeling & Architecture
• Design and maintain conceptual, logical, and physical data models for enterprise data platforms.
• Develop dimensional models using Kimball methodologies, including star schemas, fact tables, dimension tables, slowly changing dimensions (SCDs), and conformed dimensions.
• Partner with business and technical stakeholders to understand data requirements and translate them into scalable data structures.
• Evaluate source systems and define integration strategies for enterprise reporting and analytics.
• Snowflake & Data Warehousing
• Design and optimize Snowflake database structures, including schemas, tables, views, and data organization strategies.
• Collaborate with Data Engineering teams to implement efficient ELT/ETL processes.
• Support performance tuning, query optimization, clustering strategies, and cost-efficient Snowflake design.
• Participate in data platform modernization initiatives and cloud migration efforts.
• Documentation & Governance
• Create and maintain comprehensive data dictionaries, business glossaries, lineage documentation, and model diagrams.
• Document data definitions, transformation rules, business logic, and source-to-target mappings.
• Support data governance initiatives by promoting consistency, quality, and traceability across data assets.
• Ensure data models align with regulatory, security, and compliance requirements.
• Development & Technical Support
• Write and review SQL, data transformation logic, and validation queries.
• Support development of data pipelines and transformation processes using SQL and modern data engineering tools.
• Collaborate with developers and analysts to troubleshoot data quality and performance issues.
• Build reusable frameworks and standards that improve data consistency and maintainability.

Required Qualifications

• Bachelor's degree in Computer Science, Information Systems, Data Analytics, or related field.
• 5+ years of experience in data modeling, data warehousing, or data architecture roles.
• Strong expertise in dimensional modeling and Kimball data warehousing principles.
• Hands-on experience with Snowflake in a production environment.
• Advanced SQL development and query optimization skills.
• Experience creating conceptual, logical, and physical data models.
• Strong documentation skills, including data dictionaries, lineage, and technical specifications.
• Experience working with ETL/ELT processes and modern data pipelines.
• Ability to communicate complex data concepts to both technical and non-technical audiences.

Preferred Qualifications

• Experience with dbt, Matillion, Informatica, Fivetran, Airflow, or similar data integration tools.
• Experience with data cataloging and governance platforms such as Collibra, Alation, or Microsoft Purview.
• Familiarity with Data Vault modeling concepts.
• Experience with Python, PySpark, or other programming languages used in data engineering workflows.
• Experience working in Agile delivery environments.
• Knowledge of healthcare, financial services, insurance, or other highly regulated industries.

Technical Skills

• Snowflake
• SQL
• Dimensional Modeling
• Kimball Methodology
• Data Warehousing
• Data Mapping & Lineage
• Data Documentation
• Data Quality Analysis

Success Factors

• Strong analytical and problem-solving skills.
• Ability to balance business requirements with scalable technical design.
• Attention to detail and commitment to data quality.
• Excellent documentation and communication skills.
• Comfortable working across architecture, engineering, analytics, and business teams.
• Ability to influence enterprise data standards and best practices.

Nice-to-Have Profile

• A candidate who can move comfortably between architecture and implementation—someone who can design a Kimball-compliant dimensional model in the morning, document source-to-target mappings in the afternoon, and write SQL/Python code to validate and support the implementation before the day is over.