Data Modeler

Required Skills • Strong problem-solving, influencing, communication, and presentation skills; self-starter. • 7+ years of Experience in data modeling, data strategy, and roadmap for large and complex health entities and systems; implemented large-scale, end-to-end Data Management & Analytics solutions for more than one large client. • 5+ years of Strong knowledge of regulatory security requirements regarding HIPAA, PHI, PII, and other healthcare data security standards. • 5+ years of Experience with Erwin Data Model (or comparable tools such as ER/Studio, SQL Developer Data Modeler). • 5+ years of strong healthcare domain knowledge of Medicaid, Medicare, and Commercial healthcare data sets. • Expertise with normalized OLTP, OLAP, MDM, and dimensional modeling techniques — star schemas, slowly changing dimensions, role-playing dimensions, dimensional hierarchies, and data classification. • 5+ years of Expert-level SQL skills with direct experience writing complex analytic queries, stored procedures, DDL, DML, and DCL; thorough knowledge of query optimization and the ability to write to ANSI standards and review others’ code. • 5+ years of experience in Data Quality, Data Profiling, Data Governance, Data Security, Metadata Management, MDM, Data Archival, and Data Migration strategies using appropriate tools. • Demonstrated ability to work in a fast-paced, changing environment with short deadlines, interruptions, and multiple concurrent tasks/projects. • Ability to work independently with strong planning, strategy, estimation, and scheduling skills. Preferred Skills • Experience with Microsoft Azure cloud infrastructure and services (Azure Data Lake Storage, Azure Data Factory, Purview, Azure Maps, etc.). • Experience with Snowflake DBMS, including object design and performance tuning. • Experience with Power BI or Tableau. • Experience supporting State Medicaid EDW, MMIS, or federal reporting programs (T-MSIS, PERM, MARS, Quality of Care). • Exposure to Teradata Vantage 20 and modernization of Teradata workloads onto cloud platforms. • Familiarity with Delta Lake / lakehouse architecture and Microsoft Fabric. • Exposure to AI/ML and GenAI tools (e.g., GitHub Copilot, Microsoft 365 Copilot, Snowflake Cortex) for accelerating modeling, documentation, and metadata enrichment. • Hands-on experience with ETL tools (e.g., Informatica, Azure Data Factory). • Hands-on experience with BI tools and reporting software. Experience with a scripting language used for analytics such as Python or R.