FREE ACCESS
5,000–10,000 jobs/day
See all jobs on Scoutfield
Search thousands of fresh jobs every day.
Discover
- Fresh listings
- Fast filters
- No subscription required
Create a free account and start exploring right away.
Head of AI and Data Platform Engineering – Specialty Distribution
Brown & Brown Insurance. Lead the Specialty Distribution Data and AI Engineering function and define its strategy, operating model, and execution roadmap .
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, developing scalable data platforms, and implementing modern engineering practices. Proven ability to manage stakeholder relationships, drive operational excellence, and ensure compliance with data governance and security standards.
Highest-signal resume keywords
Data Engineering LeadershipAI Solutions DeliveryCloud Ecosystem ExpertiseStakeholder ManagementRegulatory Compliance
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 PracticesInfrastructure as CodePythonSQLSpark
Soft Skills
LeadershipCommunicationProblem-SolvingStakeholder ManagementCoaching
Tools & Technologies
AzureDatabricksData LakeAzure Data FactoryPower BISnowflakeAzure DevOpsTerraformBicepKey Vault
Industry Keywords
Insurance IndustryGDPRLGPDData ProtectionRegulatory Compliance
Tech Stack
Tools & technologiesAzureCloudJavaPythonSDLCSparkSQLTerraformVault.NET
About the role
Key responsibilities & impact- Lead the Specialty Distribution Data and AI Engineering function and define its strategy, operating model, and execution roadmap
- 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
- Own and evolve the Specialty Distribution Data strategy and contribute to broader Enterprise Data, AI, and Specialty Distribution AI strategies
- Develop roadmaps translating business priorities into executable data, analytics, and AI platform initiatives
- Establish architecture patterns, engineering standards, governance practices, and delivery frameworks
- Manage data and AI risk, including compliance with data, AI, security, privacy, and regulatory policies
- Partner with architecture, security, infrastructure, software engineering, analytics, and business leadership teams
- Build and lead a best-practice data and AI engineering operating model
- Ensure reliable operation of data services, platforms, pipelines, integration services, orchestration tools, reporting datasets, and supporting infrastructure
- Oversee design, build, optimization, and support of modern data pipelines
- Establish engineering practices for modular code, reusable components, automated deployments, environment management, branching strategies, CI/CD, and SDLC discipline
- Drive continuous improvement across data engineering, DevOps, data operations, platform reliability, and delivery processes
- Support 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
- 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 executives, business leaders, product owners, analytics teams, and technology partners
- Manage and prioritize backlogs 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 technical and operational inefficiencies and design 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 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
- Paid Time Off
- Holidays
- Preferred Partner Discounts