Enterprise Application and Data Architect

HealthPartners is hiring an Enterprise Application and Data Architect. This role is responsible for defining the overall architecture of HealthPartners’ applications across web platforms, administrative systems, infrastructure, and data environments. The Enterprise Architect ensures that application development and enhancements align with HealthPartners’ strategic goals and integrate smoothly within the broader technical landscape.

This role partners closely with IT leadership, the Enterprise Architecture team, and business leaders to define and advance application architecture standards, policies, and long‑term technology strategy. The architect works most directly with internal data operations/platform teams, serving as a primary thought partner on data and analytics architecture, while also collaborating with internal digital/application development teams.

This is a replacement position following the departure of a long-tenured employee. The role reports to the Director of IT Enterprise Architecture and is part of a collaborative team of five professionals, including four full-time employees and one contractor.

Required Qualifications:

• Bachelor’s Degree or equivalent experience.
• Twelve (12+) years of progressive experience in software engineering, including:
  • Four (4) years of enterprise or solution architecture capacity
  • Two (2) years of recent DataOps experience.
  • Four (4) years of project management experience
• Proficiency in various technologies (e.g., web front-end, back-end, database, OS) and programming languages (e.g., Python, Java, C#, TypeScript) and direct experience designing, building, and deploying production software systems.
• Proficiency in various database technologies and modeling, and expert level in SQL.
• Data platform experience: Working knowledge of data warehouse and data lake design - including dimensional modeling, lake/lakehouse patterns, pipeline orchestration, and data quality practices.
• Demonstrated knowledge of broad technology depth across the following domains: application architecture, data architecture / DataOps, integration/API design, and enterprise applications (ERP, EHR, CRM).
• Demonstrated experience integrating AI tools (e.g., GitHub Copilot, Claude, ChatGPT) to accelerate software development, documentation, or workflows.
• Familiarity with modern SDLC practices: CI/CD pipelines, automated testing, containerization (Docker/Kubernetes), and DevOps/DevSecOps toolchains.
• Business engagement skills: Demonstrated ability to engage directly with business stakeholders - facilitating requirements discovery, translating business needs into technology direction, and validating that solutions in flight match business intent.
• Effective communication skills across technical and non-technical audiences using verbal and written forms.
• Excellent troubleshooting and diagnostic skills

Preferred Qualifications:

• Experience in healthcare IT environments (payer, provider, or health system).
• Experience in DataOps in cloud platforms (Azure preferred).
• Hands-on experience with one or more data platform technologies: Azure Synapse Analytics, Azure Fabric, Databricks, dbt, Apache Spark, or equivalent.
• Familiarity with data governance tooling (e.g., Microsoft Purview, Apache Atlas) and data catalog/lineage practices.
• Knowledge of healthcare regulations and standards (HIPAA, HL7, FHIR, CMS interoperability rules).
• Experience leading architecture in an Agile or SAFe delivery environment - including backlog shaping, enabler stories, and embedded architecture support within delivery teams.

Hours/Location:

• M-F; core business hours
• This is a hybrid role with an expectation of being onsite 2-3 days per week. 

Responsibilities:

• Develop, maintain, and communicate enterprise architecture artifacts including reference architectures, technology roadmaps, and landscape inventories.
• Apply software engineering experience to guide application architecture decisions - including system decomposition, service design, API contracts, data modeling, and software design patterns.
• Review and influence code-level architectural decisions: framework selection, dependency management, build pipelines, automated testing s