Summary

CIBMTR is a global research registry that acquires treatment and outcomes data from transplant and cellular-therapy centers on patients who have received blood or marrow transplants, CAR-T, and gene therapies for a broad range of malignant and non-malignant indications. We curate and make data available to a worldwide network of researchers, clinicians, regulators, and other stakeholders who depend on its accuracy, completeness, and timeliness.

CIBMTR has launched an ambitious, multi-year initiative to transform and modernize its entire end-to-end data pipeline. The program includes adoption of agentic AI, migration to a lakehouse architecture, establishment of centralized metadata management, expansion of analytics capabilities, and deployment of cloud-native infrastructure.

Reporting to the Sr. IT Director, the Solutions Architect will provide senior technical leadership in documenting and validating the current-state architecture and in designing, validating, and overseeing the build-out of the future-state platform. The architect will act as a trusted technical advisor, partnering with CIBMTR vendors and IT leaders alike, translating strategic objectives into concrete, governable, and secure reference architectures spanning data, analytics, machine learning, and agentic AI. The role is equal parts design authority, technical advisor, and mentor: the architect is expected not only to shape the platform, but also to raise the capabilities of an experienced team who possess deep domain and data knowledge. Success depends on technical depth, hands-on application, sound judgment across architectural trade-offs, the ability to challenge and validate vendor designs constructively, and a genuine talent for teaching.

Primary Responsibilities

Architecture & Solution Design

• Target-state architecture. Define and evolve the end-to-end reference architecture for CIBMTR's modernized data estate, including lakehouse (e.g., medallion / Delta-style) layers, data products, semantic models, and analytics and AI consumption channels.
• Hyperscaler design & optimization. Collaborate with IT teams and vendors to design, configure, and optimize CIBMTR's cloud environment ensuring the hyperscaler architecture is right-sized for cost, performance, security, and operational simplicity. Work closely with Cloud and other technical roles to align cloud infrastructure decisions with the broader data and AI platform, driving cross-disciplinary optimization across compute, storage, networking, and managed services.
• Lakehouse migration. Lead the architectural design of the migration from the current SQL-based data warehouse to a lakehouse platform, including ingestion from treatment centers, ELT/streaming pipelines, storage and table formats, and cost and performance optimization.
• Agentic AI & ML. Establish reference architectures, patterns, and guardrails for agentic AI and machine learning — including LLM/RAG patterns, agent orchestration, tool and prompt governance, evaluation, telemetry, model monitoring, and explainability — aligned to security, privacy, and regulatory expectations.
• Metadata & governance. Architect centralized metadata management, data cataloging, lineage, and a semantic layer that turns governed data into AI-ready data products discoverable through SQL, APIs, and natural-language interfaces.
• Integration & interoperability. Design integration patterns — APIs, event-driven and streaming architectures, service interfaces — that connect source treatment-center data, internal platforms, and downstream research and analytics consumers.
• Non-functional requirements. Ensure designs meet scalability, performance, resiliency, security, privacy, and regulatory requirements, applying appropriate architectural tactics and documenting the trade-offs behind each decision.

Validation, Governance & Vendor Partnership

• Independent assurance. Serve as a trusted second set of eyes on the Integration Services consultant's designs and deliverables — reviewing, challenging, and validating architecture against CIBMTR's standards, data realities, and long-term strategy.
• Architecture governance. Lead or contribute to an architecture review process that evaluates new solutions for alignment with the target state, security and compliance requirements, and enterprise standards.
• Risk & compliance alignment. Partner with cybersecurity and data-governance stakeholders to ensure architectures honor data-protection, privacy (e.g., HIPAA / PHI handling), data-use-agreement, and model-risk considerations appropriate to a clinical research registry.
• Proofs of concept. Define, guide, and evaluate POCs and technical demonstrations that de-risk key decisions before full implementation.

Mentorship & Team Upskilling

• Capability building. Mentor and upskill data engineers, BI/analytics engineers, analysts, and other IT staff as they transition from a traditional SQL data-warehouse practice to AI-native and cloud-native ways of working.
• Patterns & enablement. Create reference implementations, reusable patterns, standards, and documentation; lead enablement sessions, code/design reviews, and pairing to embed new skills durably in the team.
• Knowledge transfer. Ensure that knowledge created with the Integration Services partner is captured internally so CIBMTR can operate and extend the platform independently over time.

Strategy, Advisory & Communication

• Trusted advisor. Advise IT leadership on architectural direction, sequencing, build-vs-buy decisions, tooling selection, and the practical implications of emerging technologies.
• Roadmap contribution. Help shape and maintain the technical roadmap for the multi-year program, balancing modernization ambitions against delivery risk and operational stability.
• Stakeholder communication. Translate complex technical concepts for both technical teams and non-technical stakeholders, building shared understanding and alignment across the program.
• Perform other duties as assigned.

Knowledge – Skills – Abilities

• Fluency in architectural trade-off analysis, reference architectures and patterns, non-functional requirements, and architecture governance.
• Strong command of lakehouse and modern data-platform concepts — table formats, ELT/ETL, batch and streaming pipelines, storage and compute optimization, and data products (e.g., Databricks/Delta Lake, or Snowflake).
• Proficiency in hyperscaler cloud architecture — primarily AWS — including infrastructure-as-code, networking, managed services, cost management, and FinOps principles; Azure or GCP experience a plus.
• Solid understanding of the ML lifecycle and MLOps, plus contemporary GenAI and agentic patterns — orchestration frameworks, vector search, prompt/tool governance, evaluation, telemetry, model monitoring, and explainability.
• Working knowledge of data governance, cataloging, lineage, metadata management, and unified access-control and policy enforcement.
• Strong SQL and proficiency in at least one general-purpose language (e.g., Python).
• Understanding of data security, privacy, and regulatory considerations for sensitive data, including PHI/HIPAA-relevant controls and de-identification approaches.
• Translates complex technical concepts clearly for both technical and non-technical audiences.
• Works effectively across engineering, analytics, security, project management, and external partners.
• Constructively challenges and validates the designs of vendors and internal teams alike.
• Balances modernization ambition with delivery risk, operational stability, and cost.

Qualifications

Appropriate experience may be substituted on equivalent basis.

Minimum Required Education: Bachelor’s degree in Computer Science, Information Systems, Data Engineering, or a related field.

Minimum Required Experience: 8 years or more in data engineering, software/data architecture, or a closely related discipline, including 3+ years in a solutions, data, or enterprise architect capacity.

Preferred Education: Master's degree               

Preferred Experience: Experience in healthcare, life sciences, clinical research, or a regulated data-sensitive domain; familiarity with clinical/research registries, outcomes data, or EHR-derived data. Demonstrated experience mentoring or providing technical leadership to engineering and analytics teams.

Preferred Certification/Licensure(s):  AWS Solutions Architect Professional or equivalent hyperscaler certification; Databricks or Snowflake data-platform certification; DAMA CDMP or AI/agentic-architecture certification.

Physical Requirements

Work requires occasionally lifting moderate weight materials, standing, or walking continuously.

Work Environment

Occasional exposure to dust, noise, temperature changes, or contact with water or other liquids. Work is performed in an environmentally controlled environment.

Sensory Acuity

Ability to detect and translate speech or other communication required. May occasionally require the ability to distinguish colors and perceive relative distances between objects. #LI-NK1

Why MCW?

• Outstanding Healthcare Coverage, including but not limited to Health, Vision, and Dental. Along with Flexible Spending options
• 403B Retirement Package
• Competitive Vacation and Paid Holidays offered
• Tuition Reimbursement
• Paid Parental Leave
• Employee & Family Assistance Program (EFAP)
• Pet Insurance
• On campus Fitness Facility, offering onsite classes
• Additional discounted rates on items such as: Select cell phone plans, local fitness facilities, Milwaukee recreation and entertainment etc.

For a brief overview of our benefits see: Benefits Overview

For a full list of positions see: MCW Careers

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