Solutions Architect

MCW

. Define and evolve the end-to-end reference architecture for CIBMTR's modernized data estate .

Posted 9/22/2026full-timeMilwaukee • Wisconsin • United StatesSeniorLeadWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and optimizing cloud environments, particularly in AWS, while leading architectural migrations and ensuring compliance with data security and regulatory standards. Proficient in developing reference architectures and patterns for modern data platforms, including lakehouse concepts and machine learning integration.

Highest-signal resume keywords

Cloud Architecture (AWS)Lakehouse Platform DesignData Governance and Metadata ManagementMachine Learning Lifecycle and MLOpsSQL and Python Proficiency

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data EngineeringSoftware ArchitectureArchitectural Trade-off AnalysisELT/ETL ProcessesData CatalogingInfrastructure-as-CodeData Security and PrivacyStreaming PipelinesCost ManagementModel Monitoring

Soft Skills

Effective CommunicationMentoring and UpskillingConstructive ChallengeCollaboration Across TeamsTranslating Technical Concepts

Industry Keywords

HIPAAPHIData Use AgreementAgentic AIData LineageOperational StabilityFinOps PrinciplesTechnical RoadmapArchitecture GovernanceReference Implementations

Tech Stack

Tools & technologies

AWSCloudCyber SecurityETLPythonSQL

About the role

Key responsibilities & impact

Define and evolve the end-to-end reference architecture for CIBMTR's modernized data estate
Design, configure, and optimize CIBMTR's cloud environment for cost, performance, security, and operational simplicity
Lead the architectural migration from a SQL-based data warehouse to a lakehouse platform
Establish reference architectures, patterns, and guardrails for agentic AI and machine learning
Architect centralized metadata management, data cataloging, lineage, and a semantic layer
Design APIs, event-driven, streaming, and service-interface integration patterns
Ensure designs meet scalability, performance, resiliency, security, privacy, and regulatory requirements
Review, challenge, and validate consultant and vendor architecture designs and deliverables
Lead or contribute to architecture review and governance processes
Partner with cybersecurity and data-governance stakeholders on data protection, privacy, HIPAA/PHI, data-use-agreement, and model-risk considerations
Define, guide, and evaluate proofs of concept and technical demonstrations
Mentor and upskill data engineers, BI/analytics engineers, analysts, and other IT staff
Create reference implementations, reusable patterns, standards, and documentation
Lead enablement sessions, code/design reviews, and pairing
Capture knowledge from the Integration Services partner for internal operation and platform extension
Advise IT leadership on architectural direction, sequencing, build-vs-buy decisions, and tooling selection
Help shape and maintain the technical roadmap
Translate complex technical concepts for technical and non-technical stakeholders
Perform other duties as assigned

Requirements

What you’ll need

Bachelor's degree in Computer Science, Information Systems, Data Engineering, or a related field
Appropriate experience may be substituted on equivalent basis
8 years or more in data engineering, software/data architecture, or a closely related discipline
3+ years in a solutions, data, or enterprise architect capacity
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, including table formats, ELT/ETL, batch and streaming pipelines, storage and compute optimization, and data products
Proficiency in hyperscaler cloud architecture, primarily AWS, including infrastructure-as-code, networking, managed services, cost management, and FinOps principles
Solid understanding of the ML lifecycle and MLOps, 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 such as Python
Understanding of data security, privacy, and regulatory considerations for sensitive data, including PHI/HIPAA-relevant controls and de-identification approaches
Ability to translate complex technical concepts for technical and non-technical audiences
Ability to work effectively across engineering, analytics, security, project management, and external partners
Ability to constructively challenge and validate vendor and internal-team designs
Ability to balance modernization ambition with delivery risk, operational stability, and cost

Benefits

Comp & perks

Outstanding healthcare coverage, including health, vision, and dental
Flexible spending options
403B retirement package
Competitive vacation and paid holidays
Tuition reimbursement
Paid parental leave
Employee & Family Assistance Program (EFAP)
Pet insurance
On-campus fitness facility with onsite classes
Discounted rates on select cell phone plans, local fitness facilities, Milwaukee recreation, and entertainment