Enterprise Data and AI Architect

Patterson Companies, Inc.•NV - Remote, NV

1d•$123,200 - $164,333

About The Position

The Enterprise Data & AI Architect defines and advances enterprise data and AI architecture strategies, standards, and frameworks to enable secure, scalable, and efficient use of data across the organization. The role covers the full lifecycle of enterprise data and AI delivery, from executive roadmap discussions to hands-on data modeling, pipeline tuning, and production support. It uses technical expertise to influence architectural decisions and lead cross-functional work that advances data accessibility, governance, and business value. The architect owns enterprise data architecture, data frameworks, and related models, including data warehouses, pipelines, and integrations across enterprise systems. The role also leads the evaluation, design, implementation, and production delivery of AI solutions and document intelligence platforms, and guides an enterprise AI automation program from opportunity identification through deployment and production support. The position provides technical leadership and mentoring, advises on data and AI strategy and roadmaps, and supports engineering best practices. It requires occasional travel, approximately 10%, and can be performed in an office or remote setting.

Requirements

Bachelor's degree in Engineering, Computer Science, or a related field, or equivalent education and/or experience.
At least 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 such as Azure Synapse, BigQuery, Snowflake, Informatica, Gemini, GPT, or 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.
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, including the ability to explain complex technical concepts clearly to non-technical audiences.
Ability to lead cross-functional initiatives, influence decisions, and lead without direct authority; strong collaboration, project management, problem-solving, and analytical skills.

Responsibilities

Define and maintain enterprise data architecture, metadata management, and governance standards and frameworks.
Build metadata-driven data lineage frameworks to improve enterprise transparency and data quality.
Translate enterprise business and data requirements for a central analytics platform and ensure its service standards and technical strategies support reliable, high-volume processing at scale.
Own end-to-end enterprise data architecture, frameworks, and models, including data warehouses, pipelines, and integrations across enterprise systems.
Lead evaluation, design, and implementation of AI solutions, ensuring compatibility, interoperability, and alignment with enterprise architecture principles.
Architect and deliver production AI solutions and document intelligence platforms for business use cases.
Lead the enterprise AI automation program, identifying high-value opportunities with business leaders and guiding solutions through design, deployment, and production support.
Design AI-driven automation for complex business processes and manage prompt design, tuning, and evaluation for consistency and accuracy.
Optimize enterprise data and information flows by reducing redundancy, improving accessibility, and balancing availability with security and governance requirements.
Architect API-driven integrations across enterprise platforms, including SAP Ariba, HighRadius, and Microsoft Graph, to enable self-service, reduce turnaround time, and automate manual processes.
Provide technical leadership, direction, and mentoring on complex architecture initiatives and advance best practices across projects and teams.
Advise cross-functional partners on data and AI strategy and technical roadmaps.
Mentor engineering teams on CI/CD, data security, code quality, and architectural best practices.
Comply with company and department policies and standards, and perform other duties as assigned.