Enterprise Data & AI Architect

At Forvis Mazars, technology is a catalyst for growth, innovation, and transformation. Firm Technology Services (FTS) sits at the intersection of business strategy and digital enablement, partnering across the firm to harness emerging technologies, advance AI-driven solutions, modernize the portfolio, and create new capabilities that accelerate operational success. Our culture is collaborative, engineering-minded, and future-focused, empowering talented professionals to solve complex challenges, challenge conventional thinking, and build solutions that make a measurable impact. This role is more than an opportunity to support a function. It is a chance to help shape the future of the firm, directly contributing to strategic growth initiatives, exceptional client experiences, and the continued evolution of a world-class technology organization.

Data is more than an enterprise asset. It is a catalyst for smarter decisions, differentiated experiences, innovation, competitive advantage, and significant growth. Our Enterprise Data & Analytics organization is building a modern, trusted data ecosystem designed to make high-quality data easier to find, govern, share, and activate across the firm.

We are seeking a forward-thinking Enterprise Data & AI Architect to help define and deliver the next generation of our enterprise architecture. This position will shape the data and AI architecture supporting the Databricks Intelligence Platform and the broader firm data strategy, creating a scalable foundation for reporting, analytics, real-time data, generative AI, AI assistants, and emerging agentic AI capabilities.

Working across business and technology teams, the Enterprise Data & AI Architect will establish architecture patterns, information models, governance principles, and platform standards that balance innovation, scalability, security, and speed to value. This is an opportunity to help shape not only a technology platform, but also how Forvis Mazars uses trusted data and AI to operate, innovate, and grow.

What You Will Do:

- Define and maintain the target architecture for enterprise data and AI, 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 from a common, governed data foundation - Establish patterns for reusable data and AI services rather than developing separate infrastructure for each AI use case - Design secure data architectures using Unity Catalog, including data-access boundaries, metadata management, row- and column-level security, lineage, and governance - Establish architecture 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 - Remain sufficiently hands-on to validate architecture patterns 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 determine 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 capabilities within the Databricks Intelligence Platform and determine their suitability for enterprise use - Coach and supervise the Databricks Platform Administrator

Minimum Qualifications:

- 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 that incorporate 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

Preferred Qualifications:

- 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