Executive Vice President, Data Transformation - Real Assets Data Steward

Fund Administration is Citco’s core business, and our alternative asset and accounting service is one of the industry’s most respected. Our continuous investment in learning and technology solutions means our people are equipped to deliver a seamless client experience. As a core member of our Data Transformation team, you will be working with some of the industry’s most accomplished professionals to deliver award-winning services for complex fund structures that our clients can depend upon. Your Role The Domain Data Steward serves as the primary bridge between a designated business domain and the Data Transformation Office. This role combines deep subject matter expertise with hands-on data governance accountability, driving the adoption of the firm's data strategy within the domain, identifying and realizing the value of more intentional data use, and ensuring that the domain's data assets are well-understood, trustworthy, and fit for purpose across the enterprise data platform. A key priority of this role is championing an AI-first approach to data stewardship — ensuring that metadata, tagging, and data assets are structured and maintained to support AI knowledge bases, retrieval systems, and automated intelligence workflows across the enterprise. Strategy & Engagement Socialize the Citco’s data strategy within the assigned domain; build awareness, understanding, and sustained buy-in among domain stakeholders and leadership Identify and surface data opportunities – process improvements, improved systems integrations, analytical use cases, reporting gaps – that can be unlocked through more intentional data management Partner with domain leaders to agree on a clear value proposition and define interim milestones that demonstrate early and ongoing return on investment Develop and maintain a current state assessment of the domain’s data landscape (sources, data flows, data quality, gaps) as the foundation for improvement planning Author and maintain the domain’s aspirational data roadmap, aligning it with the broader data strategy and enterprise platform initiatives Own and maintain the domain's section of the enterprise data dictionary — including field definitions, business rules, data ownership, PII and sensitivity tagging, and contextual usage tips — following the enterprise’s standardized format and tagging conventions to ensure compatibility with AI ingestion, RAG systems, and automated knowledge discovery Define and enforce AI-ready metadata standards — ensuring all domain data assets are tagged, classified, and documented in alignment with the enterprise AI knowledge base architecture Represent the domain on the Data Governance Committee, contributing domain expertise, sharing lessons learned, and ensuring alignment with the cross-domain governance standards Participate in governance forums, steering groups, and working sessions as the authoritative voice for the domain’s data interests Lead the domain’s integration with the enterprise Master Data Management (MDM) platform Participate in feedback loops for AI-generated outputs within the domain — reviewing accuracy, identifying metadata gaps, and iteratively refining definitions and tagging to improve retrieval quality and response fidelity Data Modeling & Platform Design Collaborate with Data Engineering and Product Owners to design end-to-end reporting data models across the medallion architecture Define and document data quality check requirements at each layer (systems of engagement, systems of record, systems of insight, etc.), including business rules, tolerance thresholds, warning and error boundaries, and remediation expectations Specify data governance requirements – retention, access controls, classification, and lineage – for the domain datasets Define and ratify data contracts with upstream data providers and downstream consumers, ensuring agreed expectations around structure, business rules, quality tolerances, and SLAs are formally documented and maintained Data Quality Management Oversee the end-to-end testing of domain data pipelines and datasets, coordinating with Data Engineering on test case design, execution, and sign-off Maintain a comprehensive data quality documentation library covering all active checks, tolerances, warning thresholds, error conditions, and remediation procedures Continually monitor and improve data quality and data health; own and maintain a data health score for each domain dataset, triage quality incidents, coordinate resolution, and track recurrence to drive root cause elimination, implement additional data quality checks Communications & Enablement Design and deliver domain-specific demos, training sessions, and documentation to drive adoption of new datasets, tools, and data practices Field domain questions related to data definitions, data availability, data quality, and platform capabilities Develop and maintain domain-level data migration plans and cutover strategy Support change management activities related to data platform transitions, ensuring domain stakeholders are informed, prepared, and interruptions limited About You 15+ years of experience in a data-focused role within or closely aligned to the relevant business domain Demonstrated subject matter expertise in the assigned domain, with the ability to translate business context into data requirements and vice versa Solid understanding of data governance principles, data quality frameworks, and data lifecycle management best practices Working knowledge of modern data platform concepts including medallion architecture, data pipelines, and data modeling Experience documenting data dictionaries, business glossaries, data quality rules, or data specifications Comfortable engaging and influencing stakeholders at multiple levels, including business leaders and technical teams Strong written and verbal communication skills with ability to present complex data topics clearly and concisely Experience with enterprise data platforms such as Databricks, Snowflake, or equivalent preferred Familiarity with AI/ML data requirements, including metadata standards for knowledge bases, vector databases, or retrieval-augmented generation (RAG) frameworks preferred Familiarity with data governance tools, data catalogs, or lineage platforms preferred Proficiency in SQL for data exploration, validation, and quality monitoring Salary Range: USD$237,000 - 354,000 Our Benefits Your well-being is of paramount importance and central to our success here at Citco. Citco offers a comprehensive and competitive total rewards package to support your career success and personal needs. Your base salary will be determined by several factors such as the role, experience, skillset, market conditions, etc. Furthermore, qualifying positions can participate in an annual discretionary bonus pool based on company profitability and individual contributions. Our comprehensive benefits package includes medical, dental, and vision coverage, short and long-term disability benefits, a retirement savings plan, tuition reimbursement, mental health and wellness support, parental leave, and more. Additional details about our total rewards package will be shared during the hiring process. At Citco, we take pride in fostering an inclusive culture by prioritizing the hiring of people from diverse backgrounds. Our culture is a source of pride and strength, fostering innovation, mutual respect, and collaboration. We warmly welcome and encourage applications from people with disabilities. If you require any accommodations to make our recruitment process more accessible for you, please let your recruiter know. As an equal opportunity employer, Citco adheres to making all employment and personnel decisions without discriminating based on race, color, creed, religion, sex, physical disability, mental disability, age, marital status, sexual orientation, citizenship status, national or ethnic origin, or any other protected status. We believe that an inclusive workforce not only enriches our company but also drives us towards greater success. Please note that this job description is not intended to be all-inclusive. Our employees may perform other job-related duties as needed to meet the ongoing needs of our organization.