Head of AI and Data Platform Engineering – Specialty Distribution

Brown & Brown Insurance

Technical leader overseeing data and AI engineering for Bridge Specialty Group's data platforms. Responsible for strategy, operations, and managing a high-performing team.

Posted 7/21/2026full-timePlano • Florida, Texas • 🇺🇸 United StatesLeadWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and executing data and AI strategies, managing large-scale data engineering teams, and delivering measurable business value through innovative data solutions. Proficient in modern data platforms, cloud ecosystems, and compliance with regulatory standards.

Highest-signal resume keywords

Data Engineering LeadershipAI Solutions DeliveryAzure Data ServicesData GovernanceStakeholder Management

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data EngineeringAI SolutionsData GovernanceData IntegrationData ModelingCloud EcosystemsCI/CD PracticesPythonSQLSpark

Soft Skills

LeadershipCommunicationProblem-SolvingStakeholder ManagementExecutive Presentation

Tools & Technologies

Azure Data FactoryDatabricksPower BISnowflakeTerraformBicepAzure DevOpsKey VaultDevSecOpsCosmos DB

Industry Keywords

Insurance IndustryRegulatory ComplianceData ProtectionGDPRLGPD

Tech Stack

Tools & technologies

AzureCloudJava.NETPythonSDLCSparkSQLTerraformVault

About the role

Key responsibilities & impact

Own and evolve the Specialty Distribution Data strategy while contributing to broader Enterprise Data, AI, and Specialty Distribution AI strategies.
Develop and maintain roadmaps that translate business priorities into executable data, analytics, and AI platform initiatives.
Establish scalable architecture patterns, engineering standards, governance practices, and delivery frameworks for data and AI solutions.
Implement extensible and reusable data products that align with enterprise models, technology standards, security controls, and platform patterns.
Manage data and AI risk, including compliance with enterprise data, AI, security, privacy, and regulatory policies.
Build and lead a best-practice data and AI engineering operating model, including team structure, processes, tools, standards, governance, and ways of working.
Ensure the reliable operation of data services, platforms, pipelines, integration services, orchestration tools, reporting data sets, and supporting infrastructure.
Oversee the design, build, optimization, and support of modern data pipelines using technologies such as Databricks, Delta Lake, Azure Data Services, Azure Data Factory, Azure Data Lake, Synapse, SQL, and related platforms.
Lead the delivery of AI solutions, AI agents, automation capabilities, and intelligent products in partnership with Enterprise AI, business teams, and platform stakeholders.
Deliver data and AI initiatives from concept through production, ensuring solutions are aligned to business priorities, enterprise standards, and measurable value.
Build strong relationships with executive stakeholders, business leaders, product owners, analytics teams, and technology partners to translate business needs into effective data and AI capabilities.
Build, lead, and develop a high-performing AI and data engineering organization capable of delivering at enterprise scale.

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 modern data platforms and cloud ecosystems, including 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 with the ability to navigate ambiguity, identify root causes across technical and organizational layers, and drive practical solutions.
Excellent leadership, communication, stakeholder management, and executive presentation skills.
Master’s degree in business, data science, computer science, information systems, engineering, or a related field. (preferred)
Experience in the insurance industry, including awareness of risk, regulatory, compliance, privacy, and data protection considerations. (preferred)
Experience securing data across multi-national environments with geo-specific regulatory requirements such as GDPR, LGPD, or similar frameworks. (preferred)
Hands-on 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
Beyond Benefits : Paid Time Off, Holidays, Preferred Partner Discounts and more.