Enterprise Data Architect

Location: New Orleans

We've made a lot of progress since opening the doors in 1942, but one thing has never changed - our commitment to serve, heal, lead, educate, and innovate. We believe that every award earned, every record broken and every patient helped is because of the dedicated employees who fill our hallways.

At Ochsner, whether you work with patients every day or support those who do, you are making a difference and that matters. Come make a difference at Ochsner Health and discover your future today!

The Data Analytics Architect designs and implements enterprise data architecture that enables advanced analytics, reporting, and data-driven decision-making across the healthcare system. This role ensures data integrity, security, and accessibility while supporting clinical, operational, and financial priorities. The architect collaborates with stakeholders to define data strategies, optimize data pipelines, and leverage modern technologies to improve patient outcomes and overall organizational performance.
To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable qualified individuals with disabilities to perform the essential duties.

This job description is a summary of the primary duties and responsibilities of the job and position. It is not intended to be a comprehensive or all-inclusive listing of duties and responsibilities. Contents are subject to change at the company's discretion.

Education

• Required
  - Bachelor's Computer Science, Information Systems, Data Science, or related field.
• Preferred
  - Master's

Work Experience

• Required - 7 years data architecture, data engineering, or advanced analytics roles within a healthcare environments.
• Preferred - 10 years in healthcare, with a strong understanding of healthcare data standards and interoperability frameworks (e.g., HL7, FHIR, X12).
  Hands on experience with Erwin or other data modeling tools.
  Excellent communication, facilitation, and technical documentation skills, with the ability to convey complex data concepts to both technical and non technical audiences.

Certifications

• Preferred
  - Certified Data Management Professional (CDMP)
• Preferred - AWS/Azure Data Architect Certification
• Preferred
  - Healthcare-specific certification (e.g. CHDA
  - Certified Health Data Analyst)

Knowledge

Skills and Abilities

(KSAs)

• Expertise in SQL, ETL tools, and data modeling. Familiarity with BI tools (Power BI, Tableau) and advanced analytics frameworks.
• Excellent communication and stakeholder management skills. Ability to build trusted relationships.
• Skilled at presenting to stakeholders across all organizational levels to strengthen alignment and understanding of analytics strategy and results.
• Expertise in Data Architecture and Data Modeling (conceptual, logical, and physical), including dimensional modeling and Master Data Management (MDM).
• Hands-on experience with cloud platforms such as Azure, AWS, or Google Cloud Platform, and modern data technologies including Snowflake, Databricks, and ETL/ELT tools such as Azure Data Factory, dbt, and PySpark.
• Strong understanding of healthcare data domains, including payer and provider data, clinical workflows, interoperability standards, and regulatory requirements.
• Advanced SQL skills, with experience in performance tuning and cost optimization in cloud data warehouse and lakehouse environments.

Job Duties

• Develops and maintains scalable data architecture frameworks that support enterprise analytics and reporting.
• Designs clinical, operational, and financial data models that comply with healthcare interoperability standards (e.g., HL7, FHIR).
• Establishes and implements best practices for data governance, data quality, and lifecycle management.
• Builds and optimizes data pipelines that support advanced analytics, machine learning, and AI initiatives.
• Partners with data scientists and analysts to ensure high-quality, accessible data for predictive modeling and population health use cases.
• Evaluates, recommends, and implements modern data platforms, including cloud…