Director, Enterprise Analytics & Data Products

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.

Requirements

• 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.
• 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 technology teams.