Advisor - Data Platform Architect

OhioHealth•WORK AT HOME - OHIO, OH

About The Position

OhioHealth is seeking an experienced Advisor, Data Platform to provide strategic and technical leadership for its enterprise data platform modernization. The role guides the design, architecture, and evolution of secure, scalable, cloud-based data platforms that enable analytics, artificial intelligence, digital transformation, and data-driven decision-making across the organization. The Advisor brings expertise in cloud architecture, data engineering, platform strategy, governance, and large-scale modernization. This position leads multi-year transformation programs that move legacy data environments toward modern, cloud-native ecosystems, and advises technology and business leaders on enterprise data platform decisions and investments. The role helps establish the data foundation for improved patient outcomes, caregiver experiences, operational efficiency, financial performance, and future AI-enabled healthcare capabilities. It partners across clinical, operational, financial, digital, technology, cybersecurity, governance, and compliance teams to deliver trusted, secure, accessible data platforms.

Requirements

Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related field.
6–8 years of experience in data architecture, data engineering, platform engineering, or enterprise data management.
7 or more years of experience designing and implementing cloud-based data platforms.
Demonstrated success leading large-scale, multi-year data modernization and transformation initiatives.
Deep expertise in modern cloud platforms such as Microsoft Azure, AWS, or Google Cloud.
Expert understanding of data warehousing, data lakes and lakehouses, data integration and ETL/ELT, metadata management, data governance, data modeling, real-time data processing, and distributed data architectures.
Experience developing enterprise architecture roadmaps and target-state strategies.
Strong executive communication and stakeholder management skills.

Nice To Haves

Master’s degree in Computer Science, Engineering, Information Systems, or a related discipline.
Healthcare industry experience, preferably within large integrated delivery networks.
Experience implementing cloud-native platforms using Azure Data Services, Databricks, Microsoft Fabric, Snowflake, or comparable technologies.
Experience enabling enterprise AI, machine learning, and advanced analytics capabilities.
Enterprise architecture certifications and cloud platform certifications.
Experience leading architecture review boards, governance councils, and enterprise transformation programs.

Responsibilities

Define and maintain the enterprise data platform strategy in alignment with OhioHealth’s digital transformation roadmap.
Lead architectural design of cloud-based data platforms for analytics, reporting, machine learning, artificial intelligence, and operational data products.
Establish target-state architectures and multi-year modernization roadmaps for data warehouses, data lakes, lakehouses, streaming platforms, and real-time analytics.
Evaluate emerging technologies and architectural patterns for healthcare innovation.
Advise on enterprise data platform decisions and investments.
Lead multi-year modernization initiatives involving cloud migration, platform consolidation, legacy system retirement, and data architecture transformation.
Develop approaches to migrate and modernize enterprise data assets while minimizing operational disruption.
Drive adoption of cloud-native capabilities, automation, platform engineering practices, and scalable architecture patterns.
Partner with technology, clinical, operational, financial, and digital teams to prioritize modernization investments and outcomes.
Establish measurable milestones, business-value realization frameworks, and modernization success metrics.
Design scalable architectures using cloud services, data integration frameworks, metadata platforms, and analytics ecosystems.
Guide implementation of data lakehouse, data mesh, data fabric, event-driven, real-time streaming, and AI/ML data platform architectures.
Establish architecture standards, design principles, and engineering best practices.
Ensure platform reliability, resiliency, security, observability, and performance.
Partner with cybersecurity, governance, and compliance teams to establish secure platform standards and align solutions with healthcare regulations and organizational security policies.
Promote metadata management, master data management, data quality, and data stewardship practices.
Design platforms that support trusted, governed, and accessible data.
Influence executives, technology teams, and business stakeholders on data strategy and modernization priorities; translate technical concepts into business outcomes and value propositions.
Build partnerships with vendors, cloud providers, and consulting partners.
Establish foundational data capabilities for advanced analytics, generative AI, machine learning, and intelligent automation.
Ensure data platforms support future AI initiatives with trusted, scalable, high-quality data assets, and identify opportunities to accelerate innovation.
Support digital transformation by reducing legacy complexity and technical debt, enabling self-service analytics and modern data products, facilitating integration of applications and acquisitions, and strengthening governance, security, and compliance while improving data accessibility.