Enterprise Data & AI Architect

Patterson Companies, Inc.•Saint Paul, MN

1d•$123,200 - $164,333•Hybrid

About The Position

The Enterprise Data & AI Architect is responsible for defining and advancing enterprise data and AI architecture strategies, standards, and frameworks that enable secure, scalable, and efficient use of data across the organization. This role is accountable for the full lifecycle of enterprise data and AI delivery, from executive roadmap discussions to hands-on data modeling, pipeline tuning, and production support. This role uses expertise to influence architectural decisions and lead cross-functional efforts to drive data accessibility, governance, and business value.

Requirements

Bachelor's Degree in Engineering, Computer Science or related field or equivalent education and/or experience
7 years of relevant experience in data architecture, data engineering, AI Architecture, and AI/ML solution delivery
Experience designing and delivering production AI solutions
Experience with data warehousing, integration, documentation, and AI tools (e.g., Azure Synapse, BigQuery, Snowflake, Informatica, Gemini, GPT, Google Document AI)
Strong proficiency in Python and SQL for data pipeline development and AI solution engineering
Proficiency with API-driven systems integration across ERP, procurement, finance, and CRM platforms
Demonstrated expertise in enterprise data architecture, data governance, metadata management, and lineage frameworks
Advanced knowledge of AI solution frameworks, model lifecycle concepts, and supporting data requirements
Ability to evaluate technology solutions and recommend enterprise-wide architectural approaches and best practices
Excellent communication, influencing, and facilitation skills; able to effectively present complex technical concepts clearly with non-technical audiences
Ability to lead cross-functional initiatives, influence decision-making and lead without direct authority; strong collaboration, project management, problem-solving and analytical skills

Responsibilities

Define and maintain enterprise data architecture and metadata management standards, frameworks, and governance standards that support scalability, security, integration, compliance, and consistent delivery
Build metadata-driven data lineage frameworks that improve transparency and data quality across the enterprise
Design, maintain, and translate enterprise business and data requirements for a central analytics platform, ensuring service standards and technical strategies enable processing high-volume data reliably at scale
Accountable for the end-to-end enterprise data architecture, data frameworks, and related data models, including data warehouses, data pipelines, and integration across enterprise systems to unify systems, process data high-volume reliably
Lead the evaluation, design, and implementation of AI solutions (e.g., large language solutions, business process automation) to ensure compatibility, interoperability, and alignment with enterprise architecture principles; architect and deliver production AI solutions and document intelligence platforms for use cases
Lead the enterprise AI automation program, identifying high-value opportunities in partnership with business leaders to guide solutions from design through deployment and production support; design AI-driven automation for complex business processes and be accountable for prompt design, tuning, and evaluation to meet business needs for consistency and accuracy
Optimize enterprise data and information flows by reducing redundancy, improving accessibility, and balancing data availability with security and governance requirements
Architect API-driven integrations across enterprise platforms (e.g., SAP Ariba, HighRadius, Microsoft Graph) to enable self-service capability, reduce turnaround time, and automate manual business processes
Provide expert technical leadership, direction, and mentoring on complex architecture initiatives, influencing architectural decisions and advancing best practices across projects and teams
Advise cross-functionally on data and AI strategy and technical roadmap, and mentor engineering teams on CI/CD, data security, code quality, and architectural best practices
Comply with Company and department policies and standards; performs other duties as assigned