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Head of AI and Data Platform Engineering – Specialty Distribution
Brown & Brown Insurance. Lead the Specialty Distribution Data and AI Engineering function .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in leading data and AI engineering initiatives, with a strong focus on strategy development, operational excellence, and stakeholder engagement. Proficient in managing complex data platforms and AI solutions while ensuring compliance and governance across enterprise environments.
Highest-signal resume keywords
Data Engineering LeadershipAI Solutions DeliveryAzure Data Services ExpertiseStakeholder ManagementDevSecOps Practices
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Data EngineeringAI SolutionsData GovernanceData IntegrationData ModelingCI/CD PracticesPythonSQLSparkInfrastructure as Code
Soft Skills
LeadershipCommunicationProblem-SolvingStakeholder ManagementCoaching
Tools & Technologies
Azure Data FactoryDatabricksPower BISnowflakeCosmos DBAzure AI FoundryTerraformBicepAzure DevOpsKey Vault
Industry Keywords
Insurance IndustryGDPRLGPDEnterprise TechnologyData Privacy
Tech Stack
Tools & technologiesAzureCloudJavaPythonSDLCSparkSQLTerraformVault.NET
About the role
Key responsibilities & impact- Lead the Specialty Distribution Data and AI Engineering function
- Define the strategy, operating model, and execution roadmap for enterprise-grade data and AI products
- Enable trusted data, analytics, reporting, insights, automation, and AI solutions that improve decision-making, operational performance, customer experience, and growth
- Oversee the design, delivery, governance, and ongoing operation of scalable data platforms, data products, AI solutions, and engineering practices
- Partner with enterprise technology, business leadership, security, analytics, and engineering teams
- Own and evolve the Specialty Distribution Data strategy and develop roadmaps for data, analytics, and AI platform initiatives
- Establish architecture patterns, engineering standards, governance practices, and delivery frameworks
- Implement reusable data products aligned with enterprise models, technology standards, security controls, and platform patterns
- Manage data and AI risk, including compliance with data, AI, security, privacy, and regulatory policies
- Build and lead the data and AI engineering operating model, including team structure, processes, tools, standards, governance, and ways of working
- Ensure reliable operation of data services, platforms, pipelines, integration services, orchestration tools, reporting datasets, and supporting infrastructure
- Oversee modern data pipelines using Databricks, Delta Lake, Azure Data Services, Azure Data Factory, Azure Data Lake, Synapse, SQL, and related platforms
- Establish modular code, reusable components, automated deployments, environment management, branching strategies, CI/CD pipelines, and SDLC discipline
- Drive continuous improvement across data engineering, DevOps, data operations, platform reliability, and delivery processes
- Support analytics and BI developers by operationalizing reporting workflows, curated datasets, semantic layers, and visualization-ready data products
- Lead delivery of AI solutions, AI agents, automation capabilities, and intelligent products
- Deploy incubated AI solutions into production and scale successful capabilities across the business
- Ensure AI products include governance, security, compliance, monitoring, responsible AI practices, and measurable business outcomes
- Support training, enablement, and adoption of Microsoft Copilot and other approved enterprise AI platforms
- Deliver data and AI initiatives from concept through production
- Build relationships with executive stakeholders, business leaders, product owners, analytics teams, and technology partners
- Manage and prioritize backlogs of enhancements, platform improvements, and new data product needs
- Support onboarding and integration of acquisitions into the company’s data, analytics, AI, and systems landscape
- Identify inefficiencies and design pragmatic solutions improving speed, quality, reliability, and scalability
- Build, lead, and develop a high-performing AI and data engineering organization
- Provide direction, coaching, performance management, and professional development
- Foster accountability, collaboration, innovation, engineering excellence, security awareness, and continuous improvement
- Champion modern data engineering, DevSecOps, cloud, and responsible AI practices
- Communicate complex technology concepts as clear business value to executives, technical teams, business stakeholders, and cross-functional partners
Requirements
What you’ll need- Bachelor’s degree in business, data science, computer science, information systems, engineering, or a related field
- 10+ years of progressive experience in data engineering, AI, analytics platforms, software engineering, technology leadership, or related roles
- Proven experience working with Director, VP, and C-suite stakeholders in a large-scale, matrixed enterprise environment
- Demonstrated success leading data, AI, engineering, or platform teams at scale, including people leadership, operating model design, and delivery accountability
- Experience managing large technology budgets, vendor relationships, delivery portfolios, and enterprise technology roadmaps
- Deep experience delivering data and AI solutions at scale with measurable business value
- Strong technical understanding of Azure, Databricks, Data Lake, Azure Data Factory, Synapse, SQL, Power BI, Denodo, Snowflake, Cosmos DB, Boomi, Azure AI Foundry, and related technologies
- Working knowledge of Python, SQL, Spark, data orchestration, data integration, data modeling, data governance, and data platform operations
- Experience implementing modern SDLC practices, including CI/CD, automated testing, branching strategies, Infrastructure as Code, environment management, and DevSecOps practices
- Strong problem-solving skills and ability to identify root causes across technical and organizational layers
- Excellent leadership, communication, stakeholder management, and executive presentation skills
- Master’s degree in a related field (preferred)
- Experience in the insurance industry (preferred)
- Experience securing data across multinational environments with frameworks such as GDPR or LGPD (preferred)
- Familiarity with Terraform, Bicep, Azure DevOps, Key Vault, Infrastructure as Code, and automated deployment practices (preferred)
- Experience mentoring or coaching teams on engineering excellence, data engineering standards, DevSecOps, platform reliability, and AI enablement (preferred)
- Software engineering background in Java, .NET, or similar enterprise application development technologies (preferred)
Benefits
Comp & perks- Health Benefits: Medical/Rx, Dental, Vision, Life Insurance, Disability Insurance
- Financial Benefits: ESPP; 401k; Student Loan Assistance; Tuition Reimbursement
- Mental Health & Wellness: Free Mental Health & Enhanced Advocacy Services
- Paid Time Off
- Holidays
- Preferred Partner Discounts
- Additional benefits may apply; enrollment waiting periods or eligibility criteria may apply, and offerings may vary by subsidiary or geographic location