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Data Architect (Azure Data Warehouse)

Duration:

6 Month Contract to

Hire Location:

Remote Non-Negotiables:

Recent Healthcare Experience Top Skills:

Prior Data Architect experience, preferably 5-7+ years Experience with EHR platforms and complex operational systems Reverse Engineering , and discovery skills Experience building data models, lineage, dictionaries, and architectural artifacts where little documentation existed beforehand Enterprise Data Architecture Design end-to-end Azure data architecture (ingestion, staging, curated, reporting layers) Define enterprise data domains (Clinical, RCM, CRM, Finance) Establish canonical data models (e.g., Patient, Encounter, Claim, Revenue) Reverse engineer and document the Avatar NX data model, including: Table structures, relationships, and data flows Enterprise ERDs and logical models Mapping vendor-specific schemas to normalized structures Interpreting and modeling data from a non-traditional database architecture (InterSystems Caché/IRIS), where the SQL layer represents an abstraction over a non-relational core, resulting in limited schema transparency, minimal documentation, and increased complexity in reverse engineering Integration Strategy Define integration patterns across: Avatar NX (EHR and billing logic) Salesforce (CRM and engagement) Financial systems (GL and revenue recognition) Standardize data contracts and exchange patterns (batch, API, event-driven) Data Governance & Standards Establish standards for naming, definitions, and data quality Implement governance for billing rules and derived logic Lead development of a data catalog, business glossary, and lineage framework Ensure reverse-engineered models are documented and version-controlled Ensure data models, pipelines, and architectural artifacts are managed using enterprise source control practices (e.g., Git) to support auditability and traceability Rule & Revenue Transparency Define architecture for rule outcome (inferred) tracking within Azure Enable reconciliation between NX and downstream financial systems Ensure billing logic is auditable, traceable, and explainable Collaboration Partner with Finance, RCM, Operations, IT, and Analytics leadership Provide architectural guidance to

Data Modelers, Developers, and DBAs Education Qualifications:

Bachelor's degree in computer science, Information Systems, Data Engineering, or a related technical field

Professional Qualifications:

7+ years in data architecture, data modeling, or enterprise data engineering Hands-on experience designing data platforms in Azure (ADF, Synapse, Data Lake, SQL) Demonstrated experience integrating EHR, CRM, and financial systems Proven experience working with EHR vendor databases (e.g., Netsmart Avatar NX, Epic, Cerner, or similar) Hands-on experience reverse engineering undocumented or poorly documented schemas, including: Identifying table relationships and key linkages Reconstructing data models from source systems Building ERDs from live databases rather than vendor documentation Experience translating complex clinical and billing data structures into usable enterprise models Ability to work with stakeholders to validate inferred logic (e.g., encounter flows, billing rules, documentation timing) Strong expertise in relational and dimensional data modeling Experience establishing canonical data models across domains (clinical, financial, operational) Experience implementing data governance frameworks, lineage, and data quality controls Advanced SQL Server expertise (querying, schema analysis, performance tuning) Experience with large, complex, highly normalized transactional systems Proficiency with source control and version management tools (e.g., Git), including branching strategies, pull requests, and versioning of data models, pipelines, and schema definitions Preferred Experience Experience in the Healthcare industry, data domains (clinical workflows, RCM, compliance) Experience supporting finance and revenue cycle reporting (AR, billing, reconciliation) Familiarity with Power BI, SSRS, or other reporting platforms Experience working in environments with limited vendor transparency or documentation

Workplace Environment:

Requires long periods of sitting (95% sitting, 5% standing) Extensive computer use

Competencies:

Technical Architecture Data Governance & Quality Business & Strategy Alignment Leadership & Influence