Enterprise Data & AI Architect

Forvis Mazars•Charlotte, NC

21h

About The Position

Forvis Mazars is seeking an Enterprise Data & AI Architect to define and deliver the next generation of its enterprise data and AI architecture. The role will shape architecture supporting the Databricks Intelligence Platform and the firm’s broader data strategy, creating a scalable foundation for reporting, analytics, real-time data, generative AI, AI assistants, and agentic AI capabilities. The architect will work across business and technology teams to establish architecture patterns, information models, governance principles, and platform standards that balance innovation, scalability, security, and speed to value. The role provides leadership across data, enterprise AI, and information architecture while remaining hands-on enough to validate patterns and resolve complex design issues. It also includes coaching and supervising the Databricks Platform Administrator. The position is part of Firm Technology Services and the Enterprise Data & Analytics organization. The role is advertised in Atlanta, Indianapolis, Kansas City, Springfield, Charlotte, Raleigh, and Dallas.

Requirements

Eight or more years of experience working with enterprise data platforms across data engineering, reporting, analytics, or architecture.
Five or more years of experience architecting enterprise data platforms using Databricks.
Hands-on architecture experience with Unity Catalog, lakehouse architecture, Medallion architecture, data modeling, data security frameworks, and reference data architectures.
Strong understanding of scalable data pipelines, orchestration, performance, and reliability.
Strong understanding of AI and machine-learning architectures.
Hands-on experience designing governed data access for AI agents, reusable agent services, tool and function interfaces, and orchestration patterns.
Strong Microsoft Azure architecture experience, particularly across networking, identity, storage, security, and Databricks integrations.
Working knowledge of Microsoft Fabric, Power BI, Microsoft Copilot, Copilot Studio, and Microsoft Foundry integration patterns.
Experience designing data security frameworks incorporating identity-based access, least-privilege principles, data classification, sensitive-data protection, and secure data and AI consumption.
Demonstrated ability to architect enterprise data and AI capabilities on Databricks.
Experience designing reusable, governed data and AI services that support multiple analytics, machine-learning, and agentic AI use cases.
Ability to translate architecture strategy and standards into implementable technical designs.
Strong communication and collaboration skills, with the ability to work across business, engineering, security, governance, and enterprise architecture teams.
Experience providing technical guidance, coaching, or supervision to technology professionals.

Nice To Haves

Bachelor’s degree in computer science, information technology, data architecture, engineering, or a related field.
Ten or more years of experience with enterprise data platforms across data engineering, reporting, analytics, and architecture.
Databricks professional certification.
Experience establishing enterprise architecture standards for data, analytics, generative AI, and agentic AI.
Experience implementing ontologies or knowledge graphs within an enterprise data environment.
Experience developing reusable AI services and governed data-access patterns for AI agents.
Experience integrating Databricks with Microsoft Fabric, Power BI, Copilot Studio, or Microsoft Foundry.
Experience leading architecture governance or solution-review processes across multiple business domains.
Experience balancing domain-specific requirements with enterprise architecture and governance standards.
Experience supervising or coaching a Databricks platform administrator or similar technical professional.

Responsibilities

Define and maintain target enterprise data and AI architecture, including reference architectures, patterns, principles, and technology standards.
Provide architecture leadership across data architecture, enterprise AI architecture, and information architecture.
Architect enterprise lakehouse solutions using Databricks, including Medallion architecture, layered data structures, reusable data products, semantic structures, and governed consumption patterns.
Design data architectures that support business intelligence, reporting, analytics, machine learning, AI assistants, and agentic AI on a common, governed data foundation.
Establish patterns for reusable data and AI services instead of separate infrastructure for each AI use case.
Design secure data architectures using Unity Catalog, including access boundaries, metadata management, row- and column-level security, lineage, and governance.
Establish patterns for governed data access by AI agents, reusable agent services, tool and function interfaces, and orchestration.
Lead architecture reviews for new data, analytics, and AI solutions to ensure alignment with enterprise standards before governed data access is provided.
Partner with engineering teams to translate architecture into implementable technical designs.
Validate architecture patterns hands-on and resolve complex design issues.
Work with Data Governance, Security, and Privacy teams to incorporate security, privacy, data quality, lineage, and governance into solution designs.
Partner with Enterprise Architecture to evaluate new data and AI capabilities and assess their potential fit for the firm.
Provide data architecture leadership across business domains while balancing service-line and domain requirements with enterprise standards.
Evaluate new Databricks Intelligence Platform capabilities for suitability for enterprise use.
Coach and supervise the Databricks Platform Administrator.