Data Architect

Mental Health Cooperative•Nashville, TN

11d•Remote

About The Position

The Data Architect is responsible for designing, developing, and supporting enterprise data solutions that enable accurate reporting, analytics, and operational decision-making. This role ensures data integrity, consistency, and accessibility across clinical, financial, and operational domains while maintaining strong standards for data governance, integration, and performance.

Requirements

Strong proficiency in SQL, data modeling, and ETL development
Working knowledge of healthcare data domains (clinical, billing, financial)
Understanding of enterprise data architecture and governance principles
Ability to manage priorities across development, production support, and project work
High school diploma or general education degree (GED)
Acceptable Criminal Background Investigation

Nice To Haves

Experience with Power BI or SSRS
Experience with HL7 or FHIR standards
Experience with APIs

Responsibilities

Design and maintain data models, transformations, and system integrations across internal and external data sources, ensuring adherence to data standards and best practices
Develop and support data warehouse structures, ETL processes, and reporting solutions (e.g., Power BI, SSRS) with a focus on performance, accuracy, and alignment with business definitions
Maintain documentation for data models, ETL processes, and reporting logic; support standardized definitions, data lineage, and consistent reporting practices
Monitor and troubleshoot ETL jobs, reporting processes, and database performance; resolve data issues and support critical operational and compliance reporting
Support internal and external data exchanges, including APIs and industry standards (e.g., HL7, FHIR), and assist with implementation and validation of new data interfaces
Partner with stakeholders to translate business needs into technical solutions and support clinical, financial, and operational reporting initiatives
Ensure adherence to HIPAA, data security standards, and regulatory requirements while supporting data validation and accuracy across deliverables
Identify and implement improvements to data quality, ETL performance, and reporting efficiency, including automation and standardization initiatives