Enterprise Data & AI Architect

Forvis Mazars, LLP•Charlotte, NC

About The Position

Forvis Mazars’ Firm Technology Services organization partners across the firm to advance technology, innovation, and digital transformation. The Enterprise Data & Analytics organization is building a modern, trusted data ecosystem that makes high-quality data easier to find, govern, share, and activate. The Enterprise Data & AI Architect will define and deliver the next generation of enterprise data and AI architecture, supporting the Databricks Intelligence Platform and the firm’s broader data strategy. The architecture will provide a scalable foundation for reporting, analytics, real-time data, generative AI, AI assistants, and agentic AI capabilities. The role works 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. It provides leadership across data, enterprise AI, and information architecture; translates architecture strategy into implementable designs; remains hands-on in validating patterns and resolving complex design issues; and coaches and supervises the Databricks Platform Administrator. Forvis Mazars, LLP is an independent member of Forvis Mazars Global and a public accounting firm with more than 7,000 team members serving clients in all 50 states and internationally. The firm describes its culture as collaborative and future-focused, with an emphasis on relationships, learning, and employee well-being. The role is listed as full-time and advertised in several U.S. locations.

Requirements

At least 8 years of experience working with enterprise data platforms across data engineering, reporting, analytics, or architecture.
At least 5 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 in 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, 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 for 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 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.
At least 10 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 in 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 supporting business intelligence, reporting, analytics, machine learning, AI assistants, and agentic AI from a common governed data foundation.
Establish reusable data and AI service patterns rather than 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 embed security, privacy, data quality, lineage, and governance into solution designs.
Partner with Enterprise Architecture to evaluate new data and AI capabilities and assess their fit for the firm.
Provide data architecture leadership across business domains while balancing domain requirements with enterprise standards.
Evaluate new capabilities within the Databricks Intelligence Platform for enterprise suitability.
Coach and supervise the Databricks Platform Administrator.