SVP, Enterprise Data Strategy & Governance

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.

- 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.

- 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.

- 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.

- 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, and business leadership to ensure AI initiatives are built upon trusted, governed, and secure data foundations.

- Monitor emerging technologies and industry trends to ensure Mariner's enterprise data strategy remains future-ready.

- Partner closely with Legal, Compliance, Risk, Audit, and Information Security to ensure enterprise data practices meet applicable regulatory, privacy, cybersecurity, supervision, and records management requirements.

- Incorporate regulatory and governance considerations into enterprise data strategy from the outset rather than as downstream review activities.

- Establish policies governing data retention, privacy, access management, PII protection, auditability, and appropriate data usage across internal and external stakeholders.

- Build strong partnerships across Technology, Operations, Innovation, Business Intelligence, Legal, Compliance, Risk, Information Security, and business leadership.

- Recommend organizational structures, governance forums, stewardship models, operating rhythms, and decision-rights frameworks that strengthen enterprise accountability.

- Lead through influence, credibility, and collaboration in a highly matrixed environment.

- Mentor enterprise architects, technical leaders, and governance stakeholders while fostering a culture that treats data as a strategic enterprise asset.

- Bachelor's degree in Computer Science, Information Systems, Engineering, Business, Data Management, or a related discipline.

- 12+ years of progressive leadership experience in enterprise data strategy, data governance, enterprise architecture, platform strategy, or related executive technology roles.

- 5+ years leading enterprise-scale data modernization, governance, or transformation initiatives across complex organizations.

- Demonstrated success designing or maturing enterprise data governance frameworks, stewardship models, metadata strategies, lineage, access controls, and enterprise data standards.

- Experience operating within regulated industries with a strong understanding of privacy, cybersecurity, compliance, auditability, and risk management.

- Demonstrated ability to influence executive leadership and drive enterprise-wide adoption of governance standards, operating models, and organizational change.

- Strong understanding of how trusted enterprise data enables AI, analytics, automation, and intelligent workflows.

- Experience in wealth management, financial services, banking, asset management, insurance, FinTech, or another highly regulated industry.

- Experience supporting AI readiness, responsible AI governance, intelligent automation, or enterprise AI enablement initiatives.

- Hands-on experience with cloud data platforms (e.g. Snowflake, Databricks, or comparable).

- Experience designing semantic layers, enterprise metadata strategies, operational data platforms, or large-scale integration architectures.

- Experience working across enterprise platforms including CRMs, ERPs, HR systems, Portfolio Management Systems, and related data architectures.

- Experience leading enterprise transformation within high-growth, acquisitive, or rapidly evolving organizations.

- Experience partnering closely with Legal, Compliance, Risk, Audit, Information Security, Technology, Innovation, and senior business leaders.

This role will initially operate as an individual contributor with broad organizational influence across data, governance, integration, and enterprise modernization initiatives. As the function matures, there is opportunity for this role to evolve into a people leadership position over time.

- Travel includes onsite visits to Mariner headquarters and other office locations for quarterly business reviews and leadership meetings

- May also include attendance at industry conferences and external events relevant to enterprise data strategy and architecture

- Frequency may increase during initial onboarding or major transformation initiatives