Data Modeler

Working with SMEs, the BI Business Analysis and BI Technology team to understand data requirements and the full attribute set for entities and dimensions;_ Converting business processes, domain specific knowledge, and information needs into a conceptual model;_ Converting conceptual models into logical models with detailed descriptions of entities and dimensions;_ Developing and maintaining conceptual, logical and physical dimensional data models to ensure the information models are capable of meeting end user and OBIEE developer needs;

Developing data models and data migration strategies utilizing sound concepts of data modeling including star schema, snowflake schema etc.

Modeling aggregation layers and specific star schemas as subject areas withing a logical and physical model_ Understand and meet referential data integrity requirements

Applying data normalization to the data models to performance requirements

Managing the flow of information between departments through the use of relational databases.

Maintaining data integrity by working to eliminate redundancy. Stays informed of the ways the organization uses its data._ Documenting decisions made in meetings and alternative solutions discussed

Five (5) years demonstrated hands-on experience with:_ developing and maintaining logical and physical dimensional data models, building data migration strategies utilizing sound concepts of data modeling for including star schema, snowflake schema etc._ Proficiency in a data modeling tool - preferably ErWin_ Relational data management disciplines and Strong design and development experience using Oracle technologies._ SQL programming_ Strong Business Intelligence tools and data analytics background and an in-depth understanding of how to design and create BI applications, and health care business intelligence reporting solutions_ Knowledge and experience working with Oracle performance views and data dictionary is mandatory_ 

Bachelors degree in business intelligence, information science, computer science, mathematics or equivalent technical training_ 

Effective communications skills and the ability to interact well with colleagues_ A strong analytics and communications background (e.g., math, statistics, quantitative methods, and verbal and writing proficiency)