Data Architect

Quality Insights,Inc• US,

3d•$110,000 - $165,000

About The Position

The Data Architect leads the design, evolution, and governance of the data architecture underlying Quality Insights' electronic quality measurement (eQM) platform. This role owns the technical architecture that allows the platform to ingest data from additional sources, achieve and maintain compliance with FHIR and related interoperability standards, and expedite implementation of new measure specification requirements. The Data Architect builds and maintains the platform's interoperability plan for electronic measurement reporting, defining how the architecture consumes data from additional sources via industry-standard formats such as FHIR, CQL, and QDM. This role also leads quarterly technical presentations on platform architecture progress, and designs and validates the data models, integration patterns, and cloud infrastructure that support platform performance, scalability, and modernization. The Data Architect collaborates with clinicians, analysts, engineers, and stakeholders to translate quality measurement and interoperability requirements into durable, well-governed data architecture.

Requirements

Demonstrated expertise in data architecture disciplines, including data modeling, master data management, data governance, and architecture design for large-scale healthcare data platforms.
Expertise in healthcare quality measurement and interoperability standards, including eCQMs, QDM, CQL, HL7 FHIR, USCDI, and TEFCA, with experience architecting FHIR resource models and CQL-based measure logic.
Strong programming and analytics skills using SQL/T-SQL, Python, R, and .NET.
Experience designing cloud data architecture using Azure technologies, including Azure Databricks and Apache Spark.
Proficiency in data architecture disciplines including RESTful API design, healthcare data integration architecture, ETL/ELT pipeline design, data warehousing, and database design.
Deep understanding of healthcare interoperability architecture, clinical data exchange, and Health Information Exchanges (HIEs).
Familiarity with security and risk management frameworks (e.g., NIST Risk Management Framework, HITRUST) as applied to healthcare data architecture and compliance.
Working knowledge of networking fundamentals (TCP/IP, DNS, VPN, and related protocols) as they pertain to secure data architecture and integration.
Experience with infrastructure-as-code and automation tooling (e.g., Terraform, Ansible) for provisioning and managing cloud data architecture.
Experience with SQL Server and Azure Synapse Analytics, including data query optimization at scale.
Experience working in an Agile development environment.
Computing Environment (CE) certification (e.g., AWS, Microsoft Azure, Linux) or equivalent demonstrated platform certification.
5+ years of experience in data architecture, healthcare analytics, health information technology, data engineering, software development, quality measurement, or a related technical field.
2+ years of experience supporting the development, implementation, validation, or maintenance of eCQMs or electronic quality measurement solutions.
Experience architecting or designing large healthcare data repositories, clinical information systems, data warehouses, and healthcare data integration technologies.
Experience developing technical solutions and collaborating with multidisciplinary teams supporting healthcare analytics, interoperability, quality reporting, or technology initiatives.
Experience with healthcare data analysis, database design, ETL/ELT processes, reporting tools, and cloud-based technologies.
Demonstrated ability to translate business, clinical, and quality measurement requirements into data architecture and technical implementation approaches.

Nice To Haves

Experience supporting VHA, VA, CMS, or other federal healthcare organizations.
Knowledge of healthcare quality and reporting programs, including MIPS, HEDIS, Joint Commission, and CMS reporting requirements.
Experience with healthcare quality reporting and performance measurement platforms.
Experience with data governance frameworks, metadata management, and enterprise architecture methodologies (e.g., TOGAF, DAMA-DMBOK).
Familiarity with AI/ML applications for healthcare analytics and quality improvement.
Relevant Azure, Databricks, cloud architecture, data architecture, or healthcare informatics certifications (e.g., Azure Solutions Architect, TOGAF, DAMA/CDMP, AWS Certified Solutions Architect, Snowflake SnowPro, or Databricks Certified Data Engineer/Architect).

Responsibilities

Lead the design and evolution of the data architecture underlying the eQM platform, including data models, integration patterns, and platform enhancements that expand the platform's ability to digest data from additional sources.
Architect FHIR-compliant data structures and API-PM integration approaches, translating CMS, NCQA, TJC, and internal measure specifications into technical designs, data models, algorithms, and implementation approaches that support measure accuracy, compliance, and reporting requirements.
Analyze healthcare data sources and perform data mapping, gap analysis, data quality assessments, and source evaluations as inputs to platform architecture; design target-state architecture and technical solutions to remediate identified gaps.
Design, develop, and govern databases, data pipelines, data integration architecture, reporting solutions, dashboards, and analytic products, ensuring architectural consistency, scalability, and reusability across quality measurement and interoperability initiatives.
Build and maintain the platform's interoperability plan for electronic measurement reporting, defining the standards-based architecture (FHIR, CQL, QDM, USCDI, TEFCA, APIs, HIEs) that governs how the platform utilizes data from additional sources to improve data availability, completeness, and quality.
Own the architecture for scalable cloud-based solutions utilizing Azure, Databricks, Spark, REST APIs, and related technologies, with accountability for platform performance, scalability, automation, security, and maintainability.
Develop and deliver quarterly architecture presentations to stakeholders demonstrating progress toward a FHIR/CQL-compliant architecture, analysis of implementation challenges and proposed resolutions, and implementation testing results and analysis.
Apply established architecture standards, quality assurance practices, integration approaches, and modernization strategies, including leading testing, validation, and proof-of-concept activities for new architecture components.
Evaluate emerging technologies and architecture patterns, including AI/ML solutions, and provide recommendations consistent with organizational governance and Trustworthy AI principles.
Serve as the data architecture subject matter expert, collaborating with clinical, technical, and operational stakeholders to translate business and clinical requirements into sound architecture decisions and effective technical solutions.
Communicate architecture decisions, technical findings, recommendations, implementation status, and risks through architecture documentation, reports, presentations, and participation in technical review and planning activities.
Contribute to monthly, quarterly, and ad hoc reports, presentations, and architecture documentation.
Identify architectural migration patterns, resolve technical dependencies, and optimize data query performance across platform data stores.
Conduct assessments of current and draft technical documentation for regulatory and standards compliance.
Participate in Agile development processes for platform enhancements, including sprint planning, backlog refinement, and iterative delivery of architecture components.
Other duties as assigned.