Technical Project Manager – Retail Data & AI Products

Brown & Brown Insurance•Daytona Beach, FL

3d•Hybrid

About The Position

Brown & Brown is seeking a Technical Project Manager – Retail Data & AI Products to join our growing team. This role will lead large-scale retail business data transformation initiatives, driving modernization of the data ecosystem using cloud and platform technologies (e.g., Azure, Google, Databricks etc.). Responsible for end-to-end program ownership, aligning business outcomes with data strategy, delivering scalable data platforms, and enabling advanced analytics, AI, and machine learning use cases across insurance operations. The ideal candidate combines strong program leadership, data platform expertise, and executive stakeholder influence, with a focus on delivering measurable business impact.

Requirements

Bachelor’s degree in computer science, Engineering, Business, or related field
8+ years of program management experience in data, analytics, or enterprise technology
Proven track record delivering complex, cross-functional data programs at scale
Strong understanding of: Data platforms (data lakes, warehouses, pipelines), Distributed systems and architecture principles
Experience with: Agile / hybrid delivery models, Program management tools (e.g., Azure DevOps)
Exceptional stakeholder management and communication skills

Nice To Haves

Experience in Finance or Broking Insurance
Exposure to: Azure, Databricks, Spark, Kafka, Snowflake, AI/ML platforms and workflows
PMP or equivalent certification
Experience with: Data governance and compliance, Cloud cost optimization (FinOps)
Large-scale enterprise transformations
Strategic thinking with execution rigor
Cross-functional leadership and influence
Ability to translate ambiguity into structured execution plans
Executive communication and storytelling

Responsibilities

Define and drive the enterprise data transformation vision and roadmap
Align data programs with business priorities
Establish governance frameworks for: Data platforms, AI/ML initiatives, Enterprise data standards
Translate strategic goals into execution-ready program plans
Own end-to-end delivery of large-scale data programs (data platforms, lakes, pipelines, AI initiatives)
Define scope, timelines, dependencies, and success criteria
Manage: Cross-team coordination (engineering, analytics, business), Risks, issues, and escalation pathways
Ensure delivery aligns with: Scalability, Reliability, Performance, Data quality and governance standards
Maintain and evolve the enterprise data program roadmap
Align delivery to build vs. buy strategy and portfolio governance
Drive prioritization based on business value and ROI
Manage delivery tracking via Azure DevOps or similar platforms
Own program budgets, forecasts, and cost tracking
Ensure financial accountability and transparency
Apply FinOps principles for cloud cost optimization
Establish and report on program KPIs and value realization
Partner with senior business leaders to align outcomes and priorities
Deliver clear, concise executive-level communication and status reporting
Translate technical progress into business impact narratives
Influence cross-functional teams without direct authority
Collaborate with Data Engineering to define: Architecture, Data pipelines, Platform roadmaps
Ensure alignment with modern data ecosystems: Azure, Snowflake, Databricks, ETL/ELT pipelines, Streaming/batch architecture’s
Drive adoption of scalable, reusable data platform capabilities
Define program level: Testing strategies, UAT frameworks, Quality standards
Ensure adherence to: Data governance, Privacy and compliance, AI governance standards
Embed observability, monitoring, and data quality controls
Leverage AI tools (e.g., Copilot, AI-assisted development) to improve delivery efficiency
Support development of AI/ML-ready data platforms
Ensure responsible AI practices and governance compliance
Drive retrospectives and continuous improvement processes
Introducing scalable delivery frameworks, tools, and best practices
Improve operational efficiency across programs
Foster a culture of accountability, transparency, and innovation