Healthcare Data Platform Architect (Director)
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Overview
Job Description
Huron helps its clients drive growth, enhance performance and sustain leadership in the markets they serve. We help healthcare organizations build innovation capabilities and accelerate key growth initiatives, enabling organizations to own the future, instead of being disrupted by it. Together, we empower clients to create sustainable growth, optimize internal processes and deliver better consumer outcomes.Health systems, hospitals and medical clinics are under immense pressure to improve clinical outcomes and reduce the cost of providing patient care. Investing in new partnerships, clinical services and technology is not enough to create meaningful and substantive change. To succeed long-term, healthcare organizations must empower leaders, clinicians, employees, affiliates and communities to build cultures that foster innovation to achieve the best outcomes for patients.Joining the Huron team means you’ll help our clients evolve and adapt to the rapidly changing healthcare environment and optimize existing business operations, improve clinical outcomes, create a more consumer-centric healthcare experience, and drive physician, patient and employee engagement across the enterprise.Join our team as the expert you are now and create your future.
The Data Platform Architect’s overarching role is translating business and product requirements into scalable platform and technology solutions. This role focuses on designing, building, and operating cloud-native data platforms and platform services rather than point solutions or single data tools. You will define platform standards, principles, and reference architectures that engineering teams use to build and operate platform capabilities. This includes software-defined platform services, APIs, authentication and authorization patterns, data access layers, context and retrieval services, and the underlying infrastructure required to scale and operate them reliably. The Data Platform Architect must demonstrate strong software engineering and distributed systems knowledge, with experience designing microservice-based platforms and self-managed cloud infrastructure. You will apply data mesh principles to enable domain-oriented data ownership, self-service platform capabilities, and federated governance. This role will also help shape a platform that is ready for AI-native and agentic analytics use cases. You will design architectural patterns that support intelligent systems delivering insights to consultants and clients, including data readiness, secure access patterns, retrieval and context delivery, and integration with model-driven and agentic workflows. You must be able to communicate platform design strategies clearly, lead architectural decisions across teams, and ensure implementations meet scalability, reliability, security, and operational requirements. A strong computer science foundation, a practical mindset toward emerging technologies, and the ability to learn and evolve with new technologies is required.RESPONSIBILITIES
Apply platform and system design principles toarchitecta scalable, cloud-native data platform supporting multiple domains and use cases.
Design and evolve platform services implemented as microservices, exposing capabilities through well-defined, API-first interfaces.
Define reference architecture patterns for platform services, APIs, authentication, authorization, data access, and context delivery.
Architect self-managed platform infrastructure in AWS, including provisioning, scaling, reliability, and operational patterns.
Translate business and strategic requirements into high-level platform designs including services, APIs, data access layers, context services, and processing workflows.
Define patterns for integrating data and processing platforms, including Snowflake and Apache Iceberg, into the broader platform architecture.
Enable data mesh adoption through self-service platform capabilities, domain-oriented ownership, and standardized integration patterns.
Design patterns for connecting authentication services to platform components such as APIs, semantic layers, data access services, and intelligent application services.
Design platform capabilities that support AI-native and agentic analytics use cases, including retrieval workflows, context services, semantic access patterns, and secure integration with model-driven components.
Define patterns for preparing data for intelligent systems, including discoverability, metadata, quality, lineage, access controls, and context retrieval.
Evaluate and apply AI-assisted engineering tooling to improve architecture,implementationvelocity, code quality, and developer productivity.
Educate, enable, and lead engineering teams in implementing platform services according to architectural standards, including the practical adoption of AI-assisted development practices whereappropriate.
Collaborate with stakeholders across Product, Engineering, Data Governance, Security, IT, and Client Services to align platform strategy and execution.
Partner with product and engineering teams toidentifywhere retrieval-based systems, agentic workflows, or intelligent platform services can create practical value for consultants and clients.
Create andmaintainplatform documentation including architecture diagrams, design standards, reference implementations, and guidance that helps teams build secure, scalable, and maintainable platform capabilities.
Evaluate andoptimizeplatform scalability, performance, cost efficiency, operational resilience, and readiness for intelligent and agentic workloads.
TRAVEL EXPECTATIONS
Ability to travel as needed up to 4 times per year.
REQUIRED EDUCATION & EXPERIENCE
8+ years of experience in platform, software, or data architecture roles.
BA or BS, preferably in Computer Science, Engineering, or a technology-based discipline.
QUALIFICATIONS
Motivated self-starter with the ability to learn quickly, make informed architectural decisions, and provide technical leadership.
Hands-onarchitectcomfortable working closely with engineers to translate requirements into production-ready platform solutions.
Strong software engineering skillset with experience in distributed systems, microservices, and platform engineering.
Experience designing and scaling self-managed platforms and shared services in cloud environments
Strong understanding of API design, authentication, authorization, secure service-to-service communication, and platform security patterns.
Ability todesign forscalability, fault tolerance, operational excellence, and production readiness.
Familiarity with data platform concepts and data mesh principles.
Experience working with modern data and processing platforms, including Snowflake and Apache Iceberg.
Strong understanding of how to prepare data and platform services for intelligent applications, including data quality, metadata, discoverability, access patterns, and context retrieval
Experience evaluating and applying emerging engineering approaches in a practical production context, including AI-assisted development tooling.
SQL and Python experience.
Infrastructure-as-code experience using tools such as Terraform or CloudFormation.
Strong computer science fundamentals.
Familiarity with AWS cloud ecosystems.
Experience with containerized and serverless architectures.
Knowledge of observability, monitoring, and operational best practices.
Familiarity with traditional application and platform design patterns.
Excellent written and verbal communication skills.
Experience working in Agile environments and with cross-functional or global teams.
Strong interpersonal and organizational skills.
Ability to manage time effectively andoperateas a technical leader.
Preferred qualifications include experience using AI-assisted engineering tools such as Claude Code or similar tools in a professional environment.
Preferred qualifications include experience helping other engineers adopt effective coding and development practices through coaching, shared patterns, standards, or enablement.
Preferred qualifications include experience designing or building retrieval-augmented generation (RAG) systems, semantic retrieval layers, context delivery services, or agentic workflows.
Preferred qualifications include familiarity with architectural considerations for LLM-powered systems, including grounding, evaluation, observability, and secure access control.
TECHNOLOGIES WE USE
Cloud (AWS) / Platform Services (APIs, Microservices) / Infrastructure as Code (Terraform, CloudFormation) / Data Platforms (Snowflake, Apache Iceberg, S3) / Data Processing (Spark, Athena, Glue) / RDBMS and NoSQL / Python / SQL / Security and Identity (IAM, OAuth2, JWT)/ AI-Assisted Engineering Tooling / Retrieval and Context Patterns / Intelligent Application and Agent Integration Patterns
The estimated base salary for this job is $175,000 - $240,000 USD. The range represents a good faith estimate of the range that Huron reasonably expects to pay for this job at the time of the job posting. The actual salary paid to an individual will vary based on multiple factors, including but not limited to specific skills or certifications, years of experience, market changes, and required travel. This job is also eligible to participate in Huron’s annual incentive compensation program, which reflects Huron’s pay for performance philosophy. Inclusive of annual incentive compensation opportunity, the total estimated compensation range for this job is $218,750 - $324,000 USD. The job is also eligible to participate in Huron’s benefit plans which include medical, dental and vision coverage and other wellness programs. The salary range information provided is in accordance with applicable state and local laws regarding salary transparency that are currently in effect and may be implemented in the future.
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Position Level
DirectorCountry
United States of AmericaAutomate your job search with Sonara.
Submit 10x as many applications with less effort than one manual application.
