Data Modeler

Data Modeler (8+ years)

• Develop conceptual, logical, and physical data models for a greenfield platform, translating business requirements into normalized (3NF) and dimensional (star/snowflake) structures aligned to source systems and analytical use cases.
• Design an enterprise canonical data model to standardize entities, attributes, and relationships across disparate source systems, enabling consistent integration and a single source of truth for shared business concepts.
• Establish data modeling standards and governance, including naming conventions, domain/data-type standards, key strategies (natural/surrogate), and modeling patterns (Kimball, Inmon) selected to fit the target architecture.
• Partner with business stakeholders and SMEs to capture entity definitions, business rules, cardinality, and grain, documenting them in a business glossary and data dictionary tied to each model layer.
• Produce physical designs optimized for the target platform (Snowflake, Redshift, Databricks, etc.), incorporating partitioning, clustering, indexing, distribution keys, and denormalization trade-offs for performance and cost.
• Define source-to-target mappings and transformation logic, collaborating with data engineers to ensure models are faithfully implemented in ELT/ETL pipelines and maintain lineage from source to consumption.
• Maintain and version models using modeling tools (Erwin, ER/Studio, SqlDBM, dbt) and integrate model changes into CI/CD and metadata-management workflows for traceability and impact analysis.
• Support master data management and data quality initiatives by defining reference data, hierarchies, conformed dimensions, and integrity constraints that reinforce enterprise data consistency.