Senior Data Modeler - Enterprise Data Warehouse - Remote

UnitedHealth Group•Chicago, IL

14h•$91,700 - $163,700•Remote

About The Position

Optum is seeking a hands-on Senior Data Modeler to support the Illinois Enterprise Data Warehouse (EDW) within the Enterprise Data Warehouse & Analytics group. The Data Modeler will work with large healthcare datasets and translate the client’s business requirements into enterprise systems, applications, and process designs for large, complex health data solutions. This role owns the design, governance, and evolution of the conceptual, logical, and physical data models that underpin the EDW platform and its modernization initiatives. It drives and supports initiatives for the IL EDW while participating in the wider EDW group’s focus areas — data usage and governance, information management, privacy and security, data analytics and visualization, and information modeling — bridging the current-state Teradata EDW to the future-state cloud (Azure / Snowflake) architecture. Working closely with data architects, ETL/data engineers, BI developers, DBAs, and business subject matter experts, the Senior Health Data Modeler ensures data structures are scalable, standards-compliant, well-documented, and aligned to enterprise and regulatory requirements across the Health and Human Services ecosystem.

Requirements

10+ years of IT experience
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 demonstrated 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
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
Expertise with normalized OLTP, OLAP, MDM, and dimensional modeling techniques - star schemas, slowly changing dimensions, role-playing dimensions, dimensional hierarchies, and data classification
Proven problem-solving, influencing, communication, and presentation skills; self-starter
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

Nice To Haves

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)
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
Familiarity with Delta Lake / Lakehouse architecture and Microsoft Fabric
Proven exposure to Teradata Vantage 20 and modernization of Teradata workloads onto cloud platforms
Proven exposure to AI/ML and GenAI tools (e.g., GitHub Copilot, Microsoft 365 Copilot, Snowflake Cortex) for accelerating modeling, documentation, and metadata enrichment

Responsibilities

Develop and deliver long-term strategic goals for data architecture vision and standards in conjunction with data users, clients, and other key stakeholders
Lead data architecture, data modeling, and data movement initiatives to enhance the data warehouse supporting analytics for Medicaid, Medicare, and Commercial healthcare data — including domains such as claims, provider, TPL, and member information subject areas
Create an end-to-end vision for how logical design translates into one or more physical databases and how data flows through successive stages
Document data architecture and the enterprise environment to maintain a current, accurate view that supports a single version of the truth and scales to future analytical needs
Analyze and translate business needs into long-term solution data models; evaluate existing data systems and work with the development team to create conceptual data models and data flows
Design and maintain conceptual, logical, and physical data models across staging, integration, and semantic/presentation layers
Develop dimensional models (Kimball star/snowflake), normalized (OLTP/3NF), OLAP, and Data Vault patterns; implement Slowly Changing Dimensions, role-playing dimensions, dimensional hierarchies, surrogate keys, and data classification
Define primary/foreign keys, indexes, partitioning, constraints, and referential integrity rules to ensure data quality and performance
Produce and maintain entity-relationship diagrams (ERDs), data flow diagrams, and model documentation using Erwin or equivalent tools
Ensure data strategies and architectures are in regulatory compliance; identify where existing policies and procedures require change or where new ones are needed
Oversee the mapping of data sources, data movement, interfaces, and analytics with the goal of ensuring data quality
Create and maintain data model and metadata policies and procedures for functional design; maintain data dictionaries, business glossaries, and lineage documentation
Support classification and protection of sensitive data (PII, PHI) in alignment with HIPAA, PHI, and SOX requirements
Provide technical recommendations and engage with ETL Architects, Business SMEs, and other stakeholders throughout the Solution/Data Architecture and implementation lifecycle to develop high-performance, highly scalable data solutions (data marts/warehouse, data mining, and advanced analytics)
Address data-related problems regarding systems integration, compatibility, and multiple-platform integration
Develop and implement key components and testing criteria to guarantee the fidelity and performance of data architecture
Communicate with the customer and project team in a timely manner and escalate issues and risks appropriately
Contribute to migration of legacy Teradata models to modern cloud platforms (Azure Synapse / Databricks Lakehouse, Snowflake)
Design target-state models leveraging medallion (Bronze/Silver/Gold) architecture, Delta Lake, and Parquet patterns
Assess existing models for modernization opportunities, redundancy, and optimization; recommend improvements to architects