Director, Enterprise Analytics & Data Products

This is a hybrid role based in  
** St. Petersburg, FL**  (minimum 50% in-office).

** Responsibilities*
* + Own the product vision, roadmap, prioritization, and execution alignment for enterprise analytics, AI-enabled data products, governed self-service analytics, and the enterprise data marketplace.

+ Define and drive the data marketplace strategy, including product cataloging, metadata, discoverability, access request patterns, usage transparency, adoption, and business value measurement.

+ Define and manage the analytics tool capabilities roadmap, ensuring platforms, tools, and user experiences evolve to make data and insights easier to discover, access, analyze, and consume.

+ Mature analytics capabilities and operating practices to promote governed, intuitive, self-service access to trusted data, insights, dashboards, analytics products, and AI-enabled decision support.

+ Partner with business stakeholders to understand decision-making needs, data consumption patterns, pain points, and opportunities to create reusable data products.

+ Translate business needs into clear, actionable requirements for data engineering, analytics, reporting, platform, governance, and AI execution teams.

+ Leverage AI to improve data discovery, insight generation, productivity, analytics workflows, documentation, and user experiences.

+ Work with AI, data science, and technology teams to shape practical AI-enabled capabilities built on trusted enterprise data.

+ Promote governed self-service access by ensuring data products are trusted, well-defined, secure, discoverable, and easy to consume.

+ Partner across business and technology teams to ensure data, analytics, AI-enabled capabilities, and marketplace access patterns are responsibly designed, appropriately controlled, and aligned to enterprise standards.

+ Define success metrics for data products, marketplace adoption, analytics consumption, quality, trust, reuse, business value, and stakeholder satisfaction.

+ Build trusted relationships with senior business and technology stakeholders and influence priorities across teams.

** Required Experience and Qualifications*
* + 10+ years of experience in data, analytics, business intelligence, data products, self-service analytics, AI-enabled solutions, or related disciplines.

+ 5+ years of leadership experience, preferably at Director level or equivalent.

+ Strong experience in wealth management, brokerage, advisory, asset management, or full-service financial services business with a strong understanding of the key data domains.

+ Proven experience leading data and analytics product capabilities such as data products, enterprise BI, self-service analytics, semantic layers, reporting platforms, or analytics modernization.

+ Must have experience with semantic layers, including ontology-driven semantic models, business-friendly metrics and definitions, and knowledge graph concepts that connect data, relationships, and business context for analytics and AI-enabled consumption.

+ Experience shaping or operating a data marketplace, data catalog, data product catalog, governed access model, or enterprise data consumption strategy.

+ Practical AI fluency, including how AI can improve data discovery, analytics, automation, requirements development, and business decision support.

+ Experience leveraging AI to maximize business value from enterprise data investments, including improving data discovery, consumption, insight generation, productivity, and adoption of data products.

+ Strong understanding of enterprise data platforms, data models, data quality, metadata, lineage, governance, access controls, and data consumption patterns.

+ Demonstrated ability to translate business needs into actionable requirements for data engineering, analytics, reporting, platform, governance, and AI delivery teams.

+ Strong stakeholder management skills with the ability to influence business and technology teams.

+ Ability to operate from vision and roadmap through detailed execution, including getting hands-on as needed to analyze and profile data, clarify requirements, identify solution options, and convert business needs into actionable work for…