Enterprise Data & AI Architect for Databricks Platform

Forvis Mazars, LLP

Indianapolis (IN)

On-site

USD 150,000 - 210,000

Full time

6 days ago

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Job summary

Forvis Mazars, LLP is seeking an Enterprise Data & AI Architect to shape the data and AI architecture across the Databricks Intelligence Platform and beyond. This role will partner with business and technology teams to establish governance, patterns, and scalable lakehouse solutions that enable reporting, analytics, real-time data, and AI capabilities.

You will lead architecture reviews, translate strategy into implementable designs, mentor the Databricks Platform Administrator, and collaborate

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.

Responsibilities

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