Cloud Infrastructure Architect

Universities of Wisconsin•Madison, WI

1d•Remote

About The Position

The Wisconsin Health Data Hub (WHDH), funded by the U.S. Economic Development Administration (EDA), is developing a secure, cloud-native data platform designed to deliver high-quality real-world data to support biomedical research, advanced analytics, and AI-driven discovery. The Cloud Infrastructure Architect provides technical leadership responsible for designing, implementing, and automating the infrastructure, deployment pipelines, and operational environment of WHDH’s data platform. This role ensures the secure, scalable, and highly available integration of infrastructure components supporting complex clinical and research data assets across a cloud-based environment. The position automates environments for advanced analytics, machine learning, and federated research capabilities while strictly maintaining compliance with HIPAA and institutional data security standards. Working closely with data solutions architects, data engineers, AI specialists, and security leaders, the Cloud Infrastructure Architect will translate architectural and operational requirements into scalable Infrastructure as Code (IaC) solutions and robust CI/CD practices that support WHDH’s long-term platform strategy.

Requirements

8 years of experience designing, implementing, and maintaining enterprise-scale cloud infrastructure and automated environments.
Expertise with cloud-native platform orchestration (e.g., AWS, Azure, GCP) and managing infrastructure for distributed data solutions or containerized environments (e.g., Kubernetes, Docker).
Experience designing secure CI/CD deployment pipelines, automation workflows, and robust infrastructure integration frameworks.
Familiarity with healthcare or biomedical research data environments and relevant regulatory security compliance (e.g., HIPAA).

Nice To Haves

Experience implementing DevSecOps practices, cloud-native security controls, and compliance-as-code within regulated healthcare data standards or interoperability frameworks.
Experience building and optimizing infrastructure to support AI/ML pipelines, MLOps, and advanced analytics workloads.
Expertise with securing and automating infrastructure for federated data platforms and multi-institutional data collaborations.
Experience working in federally funded research programs or academic research environments.
Strong documentation skills (e.g., creating architecture diagrams, runbooks) and proven technical leadership skills.

Responsibilities

Design and implement the scalable, secure, cloud-native infrastructure framework supporting WHDH’s data platform using Infrastructure as Code (IaC) principles (e.g., Terraform, CloudFormation).
Develop and maintain automated, elastic environments capable of ingesting, harmonizing, storing, and delivering massive structured and unstructured health datasets.
Optimize containerized environments and orchestration layers (e.g., Kubernetes, ECS) to seamlessly support complex research workflows and distributed computing.
Architect high-performance computing environments and automated provisioning pipelines tailored for AI, machine learning, and large-scale data analysis.
Build and manage secure, automated CI/CD pipelines for data engineering workflows, application code, and infrastructure deployments.
Enable reliable, continuous deployment methodologies that ensure zero-downtime updates and seamless system testing across health systems and research institutions.
Implement operational monitoring, logging, and alerting systems (e.g., Prometheus, Grafana, ELK stack) to proactively ensure platform reliability, uptime, and performance.
Bake strict security controls into the automated provisioning process, ensuring end-to-end alignment with HIPAA, institutional policies, and research data security standards.
Establish best practices for DevSecOps, including automated vulnerability scanning, secret management, and compliance-as-code.
Design and maintain immutable infrastructure patterns that enforce granular access control, precise audit logging, and strict data governance across the WHDH ecosystem.
Architects and manages containerized and distributed computing platforms that enable advanced analytics, machine learning, AI-driven research workloads, and high-performance data processing in secure cloud environments.
Collaborates with engineers, data scientists, architects, and research stakeholders to deliver scalable platform solutions that enable authorized users to securely access, process, and analyze distributed biomedical datasets.
Builds and optimizes observability frameworks, including monitoring, logging, alerting, and performance management solutions, to ensure system health, resiliency, and rapid incident response.
Manages, maintains, selects, and develops automation tools and infrastructure, including security configurations.
Performs integration, migration, configuration, and security of existing applications and services into automated infrastructures.
Serves as a subject matter expert to internal stakeholders, providing guidance and training to staff.
Designs and implements platform capabilities that support secure data sharing, federated access, identity and access management, and privacy-preserving workflows while maintaining rigorous security and governance controls.
Serves as technical lead for one or more aspects of the system.
Develops, programs, and/or deploys automation workflows for deployment, configuration, and/or monitoring of systems/services.
Analyzes requirements and communicates and coordinates with staff and internal stakeholders related to the system and/or project.