Faculty Manager (Healthcare Administrator)

We are seeking an experienced Data Architect to design and lead scalable, secure, and compliant data architectures that support clinical, operational, and financial analytics. This role is foundational to the organization’s data and AI strategy, ensuring that high-quality, well‑governed data enables advanced analytics, machine learning, and AI‑driven decision‑making.

JOB REQUIREMENTS

10–15 years in data engineering, data architecture, or enterprise data management Minimum years in healthcare or health IT environments 3–5 years in a Data Architect or Lead Architecture role Strong experience in healthcare data environments, including EMR/EHR systems and Epic and Cerner Proven experience enabling analytics and AI use cases through well‑designed data architecture Expertise in data modeling (dimensional, canonical, and semantic models) Experience supporting BI tools such as Microsoft Power BI and Tableau Hands‑on experience with healthcare interoperability standards (HL7, FHIR, CCD, DICOM) Experience integrating enterprise platforms such as ServiceNow Proficiency with SQL, ETL/ELT tools, and modern cloud data platforms Strong understanding of HIPAA and healthcare data privacy/security requirements

CERTIFICATION / LICENSURE

Certified Data Management Professional (CDMP) – DAMA International TOGAF Certification – The Open Group AWS Certified Solutions Architect (Associate or Professional) Microsoft Certified: Azure Data Engineer Associate Google Professional Data EngineerCertified Professional in Healthcare Information and Management Systems (CPHIMS) – HIMSS HL7 Certification – HL7 International Snowflake SnowPro Certification Optional: Power BI or Tableau certifications

SKILLS

Design and support of modern data platforms that enable AI/ML pipelines, including feature engineering and advanced analytics workflows Knowledge of AI/ML frameworks and healthcare AI use cases, including how data architecture enables model development and deployment Proficiency with real‑time streaming data technologies such as Apache Kafka Understanding of lakehouse architectures and cloud data platforms such as Snowflake Knowledge of cloud‑based data ecosystems that support scalable analytics and system integration Ability to design data models and curated datasets that enable self‑service analytics and data science consumption Knowledge of healthcare analytics domains, including population health and value‑based care initiatives Understanding of clinical terminologies and standards such as ICD‑10, SNOMED, and LOINC Knowledge of healthcare interoperability standards including HL7 and FHIR for cross‑system data integration Proficiency with business intelligence and analytics tools such as Microsoft Power BI and Tableau Ability to design scalable, high‑performance reporting and dashboarding solutions across clinical and operational domains Understanding of data integration across clinical, operational, and enterprise systems within governed and secure environments Strong knowledge of data quality, data governance, and healthcare regulatory compliance requirements Ability to establish and maintain consistent, trusted datasets that enable accelerated time‑to‑insight and AI innovation Data Engineering, Data Architecture, Enterprise Data Management #J-18808-Ljbffr Innovation At Work