Data Modeler

ollaboration Effectiveness demonstrated skill working directly with stakeholders, business partners, SMEs, systems peers, and cross-functional teams to elicit data requirements and design appropriate data models that align with business needs.Translating current and future business requirements into conceptual, logical, and physical data model designs.

Proficiency in utilizing standard data modeling tools (e.g.

Erwin, ER Studio, Toad DM, PowerDesigner, etc.).Structured execution of data analysis, data profiling, and data mapping tasks.Ensures referential integrity is maintained via data modeling design and data quality recommendations.Ensures data governance practices are followed during model creation to support efforts such as data cataloging, taxonomy, data lineage, and data quality.Designing data models for multiple distinct patterns (e.g.

relational, dimensional, hybrid) associated with data warehouse, BI, and large data applications.Creation of net new data models and extension of existing across multiple DBMS platforms (e.g.

Oracle, SQL Server, DB2, Snowflake, Teradata, NoSQL).Ability to understand and explain complex data integration and extraction transformation load processes.Demonstrated experience identifying and resolving data model performance issues to optimize database performance and enhance overall system functionality.Documenting and communicating data model designs and standards to ensure understanding and compliance with expectations for interoperability across the organization.Fluency in Python, SQL, and Unix.

High proficiency with generating complex SQL queries is required.Version control of databases and metadata management tools (e.g.

Git, Liquibase, etc).Proven communication skills illustrating ability to effectively interact with people at all levels of business and technology organizations.Experience working in an Agile environment using Lean, Kanban and Scrum practices.Insurance and Financial domain experience is highly desired.