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Brown & Brown Insurance

Provides risk management and insurance solutions

Head of AI and Data Platform Engineering - Specialty Distribution

Engineering LeadershipUpdated on Nov 13
Full-timeNo salary listed

About the Job

Requirements

  • A bachelor's degree in business, data science, computer science, information systems, engineering, or a related field is required.
  • At least 10 years of progressive experience in data engineering, AI, analytics platforms, software engineering, technology leadership, or related roles is required.
  • Experience working with Director, VP, and C-suite stakeholders in a large-scale, matrixed enterprise environment is required.
  • Demonstrated success leading data, AI, engineering, or platform teams at scale, including people leadership, operating model design, and delivery accountability is required.
  • Experience managing large technology budgets, vendor relationships, delivery portfolios, and enterprise technology roadmaps is required.
  • Deep experience delivering data and AI solutions at scale with measurable business value is required.
  • 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 is required.
  • Working knowledge of Python, SQL, Spark, data orchestration, data integration, data modeling, data governance, and data platform operations is required.
  • Experience implementing modern SDLC practices, including CI/CD, automated testing, branching strategies, Infrastructure as Code, environment management, and DevSecOps practices is required.
  • A master's degree in business, data science, computer science, information systems, engineering, or a related field is preferred.

Responsibilities

  • 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 aligned 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.
  • Partner with enterprise architecture, security, infrastructure, software engineering, analytics, and business leadership teams to ensure solutions are secure, scalable, reliable, and aligned to enterprise strategy.
  • 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 datasets, 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.
  • Establish engineering practices for 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 data and BI developers by operationalizing analytics, reporting workflows, curated datasets, semantic layers, and visualization-ready data products.
  • Lead delivery of AI solutions, AI agents, automation capabilities, and intelligent products with Enterprise AI, business teams, and platform stakeholders.
  • Deploy incubated AI solutions into production and scale successful capabilities across the business to expand adoption, value realization, and operational coverage.
  • Ensure AI products have appropriate governance, security, compliance, monitoring, responsible AI practices, and measurable business outcomes.
  • Partner with Enterprise AI and Communications teams to support training, enablement, and adoption of AI tools such as Microsoft Copilot and other approved enterprise AI platforms.
  • Deliver data and AI initiatives from concept through production, aligned to business priorities, enterprise standards, and measurable value.
  • Build relationships with executive stakeholders, business leaders, product owners, analytics teams, and technology partners to translate business needs into effective data and AI capabilities.
  • Manage and prioritize a backlog of enhancements, small changes, 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 across technical pipelines, platform operations, and engineering processes, and design solutions that improve speed, quality, reliability, and scalability.
  • Build, lead, and develop a high-performing AI and data engineering organization capable of delivering at enterprise scale.
  • Provide direction, coaching, performance management, and professional development for leaders, engineers, architects, and platform specialists.
  • Foster accountability, collaboration, innovation, engineering excellence, security awareness, and continuous improvement.
  • Champion modern data engineering, DevSecOps, cloud, and responsible AI practices across the organization.
  • Communicate with senior executives, technical teams, business stakeholders, and cross-functional partners, translating technology concepts into business value.

Desired Qualifications

  • Experience in the insurance industry, including awareness of risk, regulatory, compliance, privacy, and data protection considerations.
  • Experience securing data across multinational environments with geo-specific regulatory requirements such as GDPR, LGPD, or similar frameworks.
  • Hands-on familiarity with Terraform, Bicep, Azure DevOps, Key Vault, Infrastructure as Code, and automated deployment practices.
  • Experience mentoring or coaching teams on engineering excellence, data engineering standards, DevSecOps, platform reliability, and AI enablement.
  • Software engineering background in Java, .NET, or similar enterprise application development technologies.

About the Company

Brown & Brown Insurance

Provides risk management and insurance solutions

Brown & Brown offers risk management and insurance solutions through Retail and Specialty Distribution. It acts as a broker and advisor, matching customers with coverage, assessing risk, and coordinating policies. The company differentiates itself with a large industry presence, a culture built on integrity and the Power of WE, and a strong commitment to local communities. Its goal is to help customers manage and reduce risk while protecting their assets over the long term.

Company size
5,001-10,000
Company stage
IPO
Headquarters
Leeds, United Kingdom
Founded
1914

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