VP, Data Architecture

Vice President, Data Architecture
Department: Technology – Data Architecture
Location: Remote
FLSA Status: Exempt
People Leader: Yes
Travel: <5–10%
Summary
Company Summary
Accuity partners with hospitals and health systems through a technology-enabled, physician-led model that improves clinical documentation integrity, coding accuracy, reimbursement optimization, and quality outcomes.
Job Summary
The Vice President, Data Architecture is a hands-on technology leader responsible for defining, building, and scaling Accuity’s enterprise data platforms, data architecture, data applications, data pipelines, and analytics enablement capabilities. This role’s top priority is leading Accuity’s migration from its SQL Server based architecture to a modern Databricks lakehouse, reducing technical debt and platform cost while improving scalability and performance. Reporting to the Chief Technology Officer, this role owns the Data Engineering and Data Operations functions while also contributing directly to technical design, platform development, data modeling, database optimization, and delivery execution. The Vice President, Data Architecture partners closely with Data Science, Application Development, Operations, Finance, and other stakeholders to ensure Accuity’s data ecosystem is secure, scalable, reliable, cost-efficient, and positioned to support reporting, analytics, SaaS applications, and AI/ML enablement.
Responsibilities
Strategy and Data Architecture Leadership
• Lead the design, development, and evolution of Accuity’s Azure-based enterprise data architecture, including the migration from the SQL Server based architecture to a modern Databricks lakehouse, partnering with the CTO and Databricks on sequencing and delivery.
• Own the data platforms, data architecture, data applications, data pipelines, and analytics enablement capabilities that support Accuity’s business operations, technology platforms, reporting needs, and AI/ML enablement.
• Establish scalable data architecture standards, patterns, and governance practices to support reliable data access, integration, reporting, and analytics.
• Translate business requirements into data platform strategies, technical designs, program enhancements, and delivery roadmaps.
• Partner with the CTO and Technology leadership to prioritize data initiatives aligned with company objectives, operational needs, client outcomes, and product capabilities.
• Evaluate current and future data platform needs and recommend improvements to support scalability, reliability, automation, security, performance, and cost efficiency.
• Identify and lead initiatives to reduce data platform infrastructure and licensing costs through modernization and rationalization of the legacy stack.
Data Platform, Engineering, and Analytics Enablement
• Lead data-centric initiatives supporting SaaS applications, ETL processes, encounter-level and revenue cycle data processing, reporting engines, enterprise analytics, and future machine learning enablement.
• Design, build, and optimize data applications, data platforms, data pipelines, data warehouses, data models, data flows, and reporting infrastructure.
• Provide hands-on technical leadership for Azure database administration, database architecture, database automation, and data platform optimization.
• Develop and guide the development of database solutions used to store, retrieve, integrate, and analyze company information.
• Lead the migration and phased decommission of legacy database objects, stored procedures, views, SSIS packages, and related data assets as part of the transition to the modern data platform.
• Analyze structural requirements for new data applications, software capabilities, reporting needs, and analytics solutions.
• Improve data system performance through testing, troubleshooting, query optimization, automation, and integration of new data platform capabilities.
• Define and maintain appropriate data security, backup, recovery, and operational support procedures for assigned platforms.
• Support operational reporting and Management Information Systems needs as required.
AI/ML Enablement and Data Science Partnership
• Own the data architecture and platform capabilities required to enable AI/ML development, deployment, operationalization, and monitoring.
• Partner closely with the VP, Data Science & AI to support Accuity’s data science strategy and ensure data platforms meet model development and analytics requirements.
• Collaborate with Data Science to operationalize models by ensuring availability, quality, structure, integration, and performance of required data assets.
• Coordinate cross-functional stakeholders to launch data, analytics, and AI/ML enablement initiatives.
• Ensure clear owners