Principal Data Architect

UNITED NETWORK FOR ORGAN SHARING•n/a, OR

4d•$145,000 - $170,000•Remote

About The Position

The Principal Data Architect is the senior individual contributor accountable for data architecture across UNOS Data, AI and Analytics. The role owns end-to-end architecture for the UNOS data intelligence platform, a lakehouse unifying clinical, operational and financial data, including EMR/EHR data. The architect sets technical direction for how data is ingested, modeled, governed, secured and served, and builds the data foundation for an AI-enabled BI platform supporting analytics and agentic AI. Working closely with data engineering, data science and technology teams, this role takes a hands-on approach to setting architectural standards during the lakehouse build and stewarding the platform as it scales. It is based remotely and reports to the Director, Data.

Requirements

12 or more years in technology, including 8 or more years in data architecture, data engineering or related technical roles.
3 or more years working with healthcare data in a regulated environment, including EMR/EHR integration and HIPAA compliance.
Proven ownership of enterprise data architectures and reusable data product patterns.
Experience designing a cloud lakehouse on Azure and Databricks using medallion architecture.
Expert SQL, Python and PySpark skills.
Strong data modeling skills across dimensional, normalized, data mesh and data vault approaches.
Hands-on experience with Azure data services, including ADF, ADLS, Synapse, Azure SQL, Delta Lake and Azure Databricks.
Bachelor’s degree in Computer Science, Engineering, Information Systems, Health Informatics or a related field, or equivalent experience.

Nice To Haves

Experience with Epic Clarity/Caboodle, Oracle Health (Cerner) or MEDITECH data structures.
Experience with vector search, feature stores and MLOps for AI and agentic systems.
Exposure to Microsoft Foundry and/or Databricks Genie agents.
Exposure to Microsoft Fabric and Azure Health Data Services.
Experience with governance and master data tools such as Collibra, Informatica or EMPI solutions.
Experience with Airflow, Terraform and CI/CD for data pipelines.
Relevant industry certifications in cloud architecture (Azure, Databricks, Snowflake), data management (CDMP, TOGAF) or healthcare interoperability (HL7 FHIR).

Responsibilities

Own the enterprise data reference architecture, from ingestion to consumption, across a multi-cloud and on-premises estate.
Create conceptual and logical data models and guide their physical implementation for all data types.
Define enterprise data standards and naming conventions, enforced through automated pipeline checks.
Design integration patterns for batch, streaming, CDC, event-driven, API and file-based data, and document end-to-end data flows.
Design master and reference data for patients, providers, organizations, locations and code sets, with clear stewardship.
Establish systems of record for authoritative datasets and define how other systems consume them.
Translate business, clinical and regulatory requirements into scalable architecture.
Own the target design for the UNOS data intelligence lakehouse using medallion architecture and open formats such as Delta Lake and Apache Iceberg.
Lead EMR/EHR source discovery and integration using HL7 v2, FHIR R4 and vendor extracts.
Build and oversee production pipelines and pipeline frameworks on Azure and Databricks that capture changes, adapt to schema updates and are fully monitored.
Standardize clinical data using common models such as OMOP CDM and FHIR, and terminologies such as SNOMED CT, LOINC, ICD-10, CPT and RxNorm.
Build governance, lineage and data quality rules into the platform using Unity Catalog and Azure access controls.
Protect PHI and sensitive data through classification, masking, retention, audit trails and least-privilege access.
Design one trusted semantic and metrics layer for both BI and AI.
Prepare data architecture for AI, including model features, RAG, document intelligence, generative AI and agents.
Define data contracts and governed access for AI agents.
Set standards for testing, monitoring and responsible use of AI models and agents in production.
Partner with AI and analytics teams to deliver secure, cost-effective and scalable solutions.
Maintain the data architecture roadmap as needs evolve.
Review and approve designs, data models and pipeline changes, and guide teams through delivery.
Design for performance, availability, resilience and cost efficiency; build in observability and operational readiness; and guide optimization of systemic issues.
Define the data quality framework and resolve design-related quality issues.
Support security and privacy teams in access reviews, incidents and new regulations.
Partner with infrastructure and cloud platform teams to keep the platform aligned with enterprise standards and controls.
Evaluate tools and vendors, run proofs of concept and advise on build-versus-buy decisions.
Build reference implementations and hand validated patterns to delivery teams.
Keep architecture diagrams, decision records and specifications current.
Coach architects and senior engineers on data modeling and data architecture.
Contribute to Enterprise Architecture governance.
Track trends such as TEFCA, CMS interoperability rules and generative AI in healthcare.
Perform other duties and support additional administrative priorities as assigned, consistent with the general scope and level of the position.