Healthcare Provider Enterprise Architect

Description:


We are seeking a highly experienced Enterprise Architect with deep Data and Analytics expertise in the Healthcare Providers industry to lead the design and implementation of enterprise data solutions. The ideal candidate will have strong leadership skills, the ability to engage with client leadership, and a track record of architecting scalable, secure, and compliant data platforms. This role requires expertise in healthcare data management, interoperability, AI-driven analytics, and cloud-based data architectures to drive data-driven decision-making and innovation in healthcare organizations.

Key Responsibilities

Data Architecture & Strategy

• Design and implement scalable, secure, and compliant enterprise data architectures for healthcare providers.

• Develop and manage data platforms, data lakes, data warehouses, and real-time analytics solutions.

• Ensure data governance, quality, and interoperability across healthcare systems.

• Define and implement data strategies aligned with business objectives and regulatory requirements (HIPAA, HITECH, HITRUST, GDPR).

• Establish best practices for healthcare data ingestion, storage, transformation, and analytics.

• Architect solutions that support AI, Machine Learning, and Generative AI applications in healthcare.

Client Engagement & Leadership

• Act as a trusted advisor to client leadership on data-driven transformation strategies.

• Engage with CIOs, CMIOs, and business leaders to translate business goals into scalable data architectures.

• Lead data governance discussions, ensuring compliance with industry standards and security policies.

• Provide thought leadership on value realization from data monetization, analytics, and AI adoption.

• Present technical roadmaps, architecture recommendations, and insights to executive stakeholders.

Data Interoperability & Integration

• Lead data integration strategies between EHR/EMR systems (Cerner, Meditech, etc.), claims systems, IoMT devices, and third-party applications.

• Ensure seamless data exchange using FHIR, HL7, CDA, X12, DICOM, and other healthcare interoperability standards.

• Architect real-time and batch data pipelines for analytics, AI, and operational workflows.

• Enable cloud-based data platforms (AWS, Azure, GCP) with hybrid and multi-cloud strategies.

Advanced Analytics & AI Integration

• Design data architectures that support predictive analytics, AI-driven clinical insights, and generative AI use cases.

• Implement data pipelines for machine learning and AI applications, ensuring scalability and compliance.

• Enable real-time and near-real-time analytics for population health, precision medicine, and clinical decision support.

• Work with data scientists and AI engineers to optimize model training, deployment, and monitoring in healthcare environments.

Governance, Security, & Compliance

• Establish data governance frameworks, ensuring data integrity, lineage, and access control.

• Ensure compliance with HIPAA, HITECH, HITRUST, GDPR, and other regulatory requirements.

• Implement data security best practices, including encryption, access control, and auditing.

• Develop and enforce metadata management and master data management (MDM) strategies.

Required Qualifications

10+ years of Total experience with minimum of 5+ recent years in Healthcare Provider industry.

Technical Skills

• Enterprise Data Architecture: Expertise in designing scalable data platforms for healthcare.

• Healthcare Data Standards & Compliance: Strong knowledge of FHIR, HL7, DICOM, ICD-10, SNOMED, LOINC, HIPAA, HITECH, HITRUST.

• Cloud & Big Data: Experience with AWS (Redshift, S3, Glue), Azure (Synapse, Data Factory), GCP (BigQuery, Dataflow).

• Data Engineering: Proficiency in SQL, Spark, Hadoop, Kafka, Airflow, ETL/ELT pipelines.

• Interoperability & Integration: Experience with EHR integration, APIs, and real-time streaming.

• AI & Generative AI: Understanding of AI-driven analytics, NLP in clinical documentation, predictive modeling, and generative AI in healthcare workflows.

• Master Data Management (MDM) & Metadata Management: Experience in data cataloging, governance, and data lineage tracking.

• Security & Compliance: Expertise in data privacy, encryption, access control, and regulatory compliance.

Leadership & Soft Skills

• Client Leadership Engagement: Ability to articulate data strategies to C-level executives and business leaders.

• Strategic Thinking: Experience in defining enterprise-wide data roadmaps and data-driven transformation strategies.

• Cross-functional Collaboration: Ability to work with clinical, operational, AI, and IT teams.

• Decision Making & Problem-Solving: Strong analytical skills to identify risks, trade-offs, and optimal solutions.

• Mentorship & Team Leadership: Guide and mentor data engineers, data scientists, and analytics teams.

• Excellent communication, stakeholder management, and people skills.

Preferred Qualifications

• Certifications: AWS/Azure/GCP Data Architect, TOGAF, HITRUST, AI/ML certifications in healthcare.

• Knowledge of Generative AI in clinical documentation automation, medical imaging AI, patient engagement chatbots.

• Understanding of Business Models in healthcare providers (hospitals, clinics, telemedicine, value-based care).

Salary range: $123,000 - $171,000 a year