Principal Data Architect

Brown & Brown Insurance•Daytona Beach, FL

9d•Onsite

About The Position

Brown & Brown is seeking a Principal Data Architect for its Retail Technology Data & AI organization. The role supports retail-wide data and AI initiatives spanning investment platforms and portfolio operations, and serves as a senior individual-contributor technical authority and strategic design leader for the Retail data platform and AI ecosystem. The architect defines cohesive, scalable, secure architecture across data platforms, AI/ML systems, governance frameworks, and integration patterns, aligned with business and product strategy. The position sets technical direction, establishes engineering standards, guides platform decisions, and advises Retail technology leadership and business domain leaders. It combines long-term strategic planning with hands-on design validation, prototyping, and guidance through complex delivery challenges. The role owns the Retail data and AI architecture blueprint and target-state roadmap; architects a hybrid platform using Microsoft Azure, Databricks, and Google; and establishes patterns for data products, Lakehouse, integration, governance, security, and AI/ML. It also defines AI/ML and MLOps architecture, including generative AI and LLM systems, and establishes governance and model risk controls. The architect leads design reviews, maintains reusable reference architectures and engineering standards, mentors technical teams, and collaborates with business, enterprise technology, security, and vendor stakeholders. The role is based in Atlanta, GA; Dallas, TX; or Daytona Beach, FL.

Requirements

Bachelor’s degree in computer science, Information Systems, Data Engineering, or a related technical field.
At least 7 years of progressive experience in data architecture, data engineering, or enterprise architecture roles.
At least 4 years in a senior or lead architect capacity.
Demonstrated experience designing and delivering enterprise-scale data platforms in cloud environments.
Proven experience architecting production AI/ML systems, including MLOps pipelines, LLM-powered applications, and agentic frameworks.
Significant experience in financial services, insurance, or similarly regulated industries.
Experience working directly with senior business leaders as a technical advisor and architecture authority.

Nice To Haves

Master’s degree is strongly preferred.
Strong preference for experience with Microsoft Azure, Google, and Databricks.
Broking domain experience is strongly preferred.

Responsibilities

Define and own the Retail data and AI architecture blueprint for ingestion, storage, transformation, serving, governance, and AI/ML deployment.
Establish the target-state architecture and a pragmatic roadmap across cloud platforms, data products, AI systems, and integration patterns.
Lead architecture governance by chairing design reviews, evaluating technology proposals, and enforcing standards.
Translate business strategy and regulatory obligations into documented architectural decisions and tradeoffs.
Serve as the technical liaison among Corporate, Retail IT leadership, and enterprise architecture functions.
Architect and evolve the hybrid data platform on Microsoft Azure, Databricks, and Google for batch, streaming, and real-time workloads.
Design Medallion architecture and enforce Lakehouse practices, including Delta Lake, Unity Catalog, and Data Mesh-aligned data product publishing.
Define consistent data modeling standards across entities.
Oversee reference MDM platform architecture and integration with policy systems, analytics, and the Lakehouse.
Design enterprise integration patterns, including API-first, event-driven, ETL/ELT, and integrations with internal and external source systems.
Ensure platform architecture addresses availability, disaster recovery, scalability, and cost efficiency for a regulated insurance environment.
Define Retail AI/ML architecture for model development, training, deployment, monitoring, and governance using Databricks Mosaic AI, Azure Machine Learning, and Azure OpenAI.
Architect MLOps capabilities, including ML CI/CD, feature stores, model registries, experiment tracking with MLflow, and production model serving.
Design generative AI and LLM architectures, including RAG systems, agentic frameworks, prompt management, and responsible AI guardrails for insurance use cases.
Establish AI governance and model risk management frameworks that support explainability, auditability, and regulatory compliance.
Evaluate and recommend foundational models, AI platforms, and emerging technologies.
Design enterprise data governance architecture covering cataloging, lineage, classification, quality, and stewardship workflows.
Define data access control and security architecture, including RBAC, ABAC, row- and column-level security, masking, and encryption.
Ensure architecture adheres to regulatory and compliance requirements and supports audit trails and regulatory examinations.
Define and maintain data and AI engineering standards for coding, design, testing, CI/CD, and documentation.
Create and curate reusable reference architecture patterns for ingestion, transformation, serving, AI deployment, and integration.
Conduct architecture reviews and design critiques, balancing technical rigor with delivery pragmatism.
Mentor and coach senior data engineers, ML engineers, and domain architects.
Monitor the data and AI technology landscape and recommend platform evolution.
Partner with business leaders to translate domain data needs into durable architectural solutions.
Collaborate with Enterprise IT, Enterprise Architecture, Information Security, and Vendor Management to align architecture with enterprise standards and procurement strategy.
Represent data and AI architecture in vendor evaluations, RFPs, and technology due diligence, assessing platform capabilities, integration complexity, and total cost of ownership.
Produce executive-ready architecture documentation and roadmaps for Retail Data & AI and senior leadership.