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ABOUT THE ROLE Mariner is seeking an accomplished enterprise data executive to define and execute the data strategy required to support the firm's long-term business objectives, AI ambitions, and future operating model. This leader will shape how enterprise data is governed, integrated, trusted, accessed, interpreted, protected, monitored, and leveraged across the organization. As AI, automation, digital workers, and intelligent workflows become increasingly embedded in how work gets done, this role will establish the trusted data foundation, governance model, and enterprise standards necessary to enable those capabilities safely and at scale. This is not a traditional Business Intelligence, reporting, or enterprise architecture leadership role. Business Intelligence, Engineering, Platform, Data Engineering, Technology, and Analytics teams will remain critical partners. The primary mandate of this role is to define the enterprise governance framework, operating model, semantic architecture, and data strategy that enables Mariner to treat data as a strategic enterprise asset. Working across Operations, Technology, Innovation, Information Security, Legal, Compliance, Risk, Business Intelligence, and business leadership, this executive will help position Mariner for the next generation of enterprise intelligence. KEY RESPONSIBILITIES ENTERPRISE DATA STRATEGY - Develop and execute Mariner's enterprise-wide data strategy using a future-back perspective aligned with the firm's long-term business and technology objectives. - Define the enterprise data operating model, including governance, ownership, stewardship, integration, access, protection, and lifecycle management. - Evaluate the current enterprise data landscape, identifying opportunities to improve data quality, governance, interoperability, scalability, and business value. - Translate long-term strategy into a practical, phased roadmap with measurable milestones and business outcomes. - Consult on the evaluation and onboarding of new platforms and vendors, establishing enterprise standards for data integration, ownership, governance, and interoperability before implementation. DATA GOVERNANCE & ENTERPRISE INTELLIGENCE - Establish enterprise standards for metadata, lineage, stewardship, classification, ownership, quality, access controls, and accountability. - Define enterprise data domains, semantic standards, reusable data products, and common business definitions that improve consistency across the organization. - Develop governance principles supporting both human and AI-enabled interactions with enterprise data. - Ensure enterprise data is trusted, discoverable, auditable, and appropriately governed for operational, analytical, regulatory, and AI-enabled use cases. - Establish measurable standards for data quality, completeness, consistency, timeliness, and fitness for purpose. ENTERPRISE ARCHITECTURE & INTEGRATION STRATEGY - Define enterprise standards for data integration, interoperability, orchestration, and information architecture across platforms and business functions. - Guide buy-versus-build decisions for enterprise data platforms, governance capabilities, integration technologies, metadata management, and orchestration tools. - Develop reference architectures that support AI readiness, operational scalability, enterprise analytics, and future-state intelligence capabilities. - Ensure enterprise systems, workflows, and integrations support the consistent, secure, and governed movement of information across the organization. AI & EMERGING TECHNOLOGY ENABLEMENT - Define the enterprise data strategy required to support responsible AI adoption, automation, digital workers, and agentic workflows. - Establish governance models for trusted AI-enabled data access, permissions, semantic understanding, lineage, explainability, and auditability. - Partner with Innovation, Technology, Legal, Compliance, Information Security,