Senior Data Architect

Description The Senior Data Architect is responsible for enterprise data architecture, analytics, business intelligence, and data platform modernization initiatives across clinical, operational, financial, and regulatory domains. This role designs, develops, and maintains scalable data warehouses, data marts, lakehouse, integration pipelines, and reporting solutions that transform complex healthcare data into trusted, actionable insights for strategic decision-making. Serving as a bridge between business stakeholders and technical teams, the Senior Data Architect partners with clinical, operational, finance, quality, research, and executive leadership to deliver enterprise analytics capabilities, data governance frameworks, and modern reporting solutions. The role plays a critical part in ensuring data quality, compliance, and usability while enabling data-driven decision-making throughout the organization. The ideal candidate combines deep expertise in healthcare information systems, data engineering, business intelligence, enterprise reporting, and data governance with strong leadership and communication skills. This position also is responsible for the modernization of legacy data platforms by leveraging cloud-based analytics technologies such as Microsoft Fabric or Snowflake, while developing enterprise Power BI solutions that support organizational growth, regulatory requirements, operational excellence, and measurable business outcomes.

Key Responsibilities

Enterprise Data Architecture & Strategy

• Design, develop, and maintain enterprise data architecture supporting clinical, financial, operational, quality, research, and regulatory reporting.
• Architect and manage enterprise data warehouses, lakehouses, operational data stores, and subject-area data marts.
• Define enterprise data standards, data models, metadata frameworks, and data governance practices.
• Develop long-term data architecture roadmaps aligned with business goals and organizational strategy.
• Evaluate emerging technologies and recommend modern platforms that improve scalability, performance, and analytics capabilities.

Data Engineering & Integration

• Architect and develop scalable ETL/ELT solutions that integrate data from multiple enterprise systems.
• Design and maintain robust data pipelines supporting healthcare, financial, operational, research, and external reporting requirements.
• Integrate and transform data from EHR systems, ERP applications, survey platforms, quality management systems, research databases, and third-party applications.
• Optimize database performance, stored procedures, data models, and data processing workflows.
• Ensure enterprise data assets are standardized, validated, and analytics ready.

Data Warehouse Modernization & Cloud Analytics

• Lead modernization initiatives that transition legacy data warehouse environments to modern cloud-based analytics platforms.
• Design and implement solutions leveraging Microsoft Fabric, OneLake, Data Factory, Lakehouse, Data Warehouse, Power BI, Snowflake, and other modern analytics technologies.
• Develop scalable architectures that support real-time analytics, self-service reporting, advanced analytics, and future AI initiatives.
• Evaluate migration strategies for legacy ETL processes, reporting environments, and data marts.
• Establish best practices for cloud data management, governance, security, and performance optimization.

Business Intelligence & Power BI

• Design, develop, and maintain enterprise Power BI dashboards, reports, scorecards, and executive analytics solutions.
• Create semantic models, reusable datasets, KPIs, and data visualizations that enable consistent reporting across the organization.
• Implement Power BI governance standards, security models, deployment processes, and performance optimization practices.
• Develop and support self-service analytics capabilities for business users and leadership teams.
• Partner with stakeholders to define reporting requirements and deliver actionable insights through modern visualization technologies.
• Maintain and enhance enterprise business intelligence platforms including Power BI, Qlik Sense, SSRS, Crystal Reports, and other reporting solutions.

Clinical Analytics & Healthcare Reporting

• Design and support analytics solutions for behavioral healthcare, population health, quality improvement, patient outcomes, and performance measurement initiatives.
• Develop reporting frameworks for clinical quality measures, productivity metrics, patient experience, crisis services, and outcome tracking.
• Support reporting and analytics for federal, state, regulatory, accreditation, and grant-funded programs.
• Collaborate with clinical and operational leaders to identify meaningful metrics that improve organizational performance and patient care.
• Ensure reporting methodologies align with industry standards and organizational objectives.

Financial & Operational Analytics

• Develop enterprise reporting solutions supporting revenue cycle, billing, claims, reimbursement, general ledger, and financial performance management.
• Design operational dashboards and scorecards supporting workforce management, productivity, service delivery, and strategic planning.
• Enable leadership visibility into financial and operational performance through trusted, enterprise-wide analytics.

Data Governance, Quality & Compliance

• Establish and maintain enterprise data governance frameworks and stewardship practices.
• Develop data validation, quality assurance, reconciliation, and auditing processes.
• Ensure compliance with regulatory requirements, reporting standards, and organizational policies.
• Promote data integrity, consistency, accuracy, and transparency across all reporting and analytics environments.
• Lead initiatives to improve data literacy and adoption across the organization.

Leadership & Stakeholder Collaboration

• Serve as a trusted advisor to executive, clinical, operational, finance, and research leadership teams.
• Translate complex business requirements into scalable data architecture and analytics solutions.
• Lead cross-functional projects involving data integration, reporting modernization, and analytics transformation.
• Mentor analysts, developers, and data professionals on architecture, reporting, and data management best practices.
• Drive a culture of data-informed decision-making throughout the organization.

Requirements

Required Qualifications Education

• Bachelor’s degree in computer science, Information Systems, Engineering, Healthcare Informatics, Data Analytics, or a related field.
• Master's degree preferred.

Experience

• 10+ years of progressive experience in data architecture, data engineering, business intelligence, analytics, or enterprise reporting.
• Significant experience designing and supporting enterprise data warehouses and analytics platforms.
• Experience working with healthcare, behavioral healthcare, clinical, financial, or regulated data environments.
• Demonstrated success delivering enterprise reporting and analytics solutions supporting executive decision-making.

Technical Expertise

• Data Architecture & Engineering
• Enterprise Data Warehousing
• Data Modeling
• Data Marts
• Lakehouse Architecture
• ETL/ELT Development
• Data Integration
• Metadata Management
• Data Governance

Database Technologies

• Microsoft SQL Server
• Oracle
• PostgreSQL
• InterSystems Cache/IRIS
• Stored Procedures
• SQL Performance Tuning

Modern Analytics Platforms

• Microsoft Fabric
• Snowflake
• Azure Data Services
• Cloud Data Platforms
• Enterprise Analytics Architectures

Business Intelligence & Visualization

• Power BI
• Qlik Sense
• SSRS
• Crystal Reports
• Dashboard Development
• KPI Design
• Data Visualization

Healthcare Systems

• Electronic Health Records (EHR)
• Clinical Data Management
• Quality Measures Reporting
• Regulatory Reporting
• Research Data Platforms
• Healthcare Analytics

Preferred Qualifications

• Experience architecting Microsoft Fabric or Snowflake data platforms.
• Experience implementing enterprise Power BI governance and self-service analytics strategies.
• Knowledge of healthcare quality measures, value-based care, CCBHC reporting, and clinical outcomes analytics.
• Experience with advanced analytics, statistical analysis, or data science initiatives.
• Familiarity with AI-enabled analytics and modern data platform capabilities.