Head of AI and Data Platform Engineering - Specialty Distribution
On-siteDaytona Beach, Florida, United States or Plano, Texas, United States
Job Summary
Own and evolve the Specialty Distribution Data strategy while developing 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, ensuring compliance with enterprise data, AI, security, privacy, and regulatory policies. Build and lead a best-practice data and AI engineering operating model, overseeing the design, build, optimization, and support of modern data pipelines using technologies such as Databricks, Delta Lake, Azure Data Services, and Synapse. Drive the delivery of AI solutions, AI agents, and automation capabilities in partnership with Enterprise AI, business teams, and platform stakeholders to expand adoption and value realization. Lead a high-performing AI and data engineering organization, providing clear direction, coaching, and performance management for leaders, engineers, architects, and platform specialists. Manage and prioritize a backlog of enhancements, small changes, platform improvements, and new data product needs while supporting onboarding and integration of acquisitions.
Required Qualifications
- 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
Desired Qualifications
- Master's degree in business, data science, computer science, information systems, engineering, or a related field
- Experience in the insurance industry, including awareness of risk, regulatory, compliance, privacy, and data protection considerations
- Experience securing data across multi-national 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
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