Head of Data Management - Managing Director (NY)

KBRA•New York, NY

3d•$225,000 - $300,000•Hybrid

About The Position

KBRA is seeking a senior leader to head our Data Management organization. Based in New York and reporting to the Chief Technology Officer, this individual will be responsible for defining and executing KBRA's enterprise data management strategy, leading Data Operations, advancing data governance and quality, and helping unlock the commercial value of KBRA's data assets. The role will work across analytical, business, product, and technology teams to establish how KBRA's data is organized, governed, curated, maintained, and made available for internal and external use. This is a highly visible leadership position requiring both strategic thinking and a willingness to engage directly in the details. The Head of Data Management will establish the operating model, standards, and capabilities necessary to manage KBRA's data as a strategic enterprise asset. You will lead the Data Operations organization and oversee disciplines including data stewardship, master and reference data management, taxonomy and ontology development, data quality, and data-provider management. Working closely with Engineering and Product, you will help establish scalable data models, standards, processes, and technology capabilities that make KBRA's data easier to discover, integrate, govern, and use. You will also partner with business leadership to identify opportunities to package and commercialize KBRA's proprietary data assets and to ensure those assets are supported by appropriate governance, quality, and operational processes.

Requirements

Bachelor's or master's degree or equivalent relevant experience.
15+ years of experience in data management, data strategy, data operations, data governance, or related disciplines.
Significant leadership experience building and managing data teams and capabilities.
Experience within financial services, capital markets, ratings, financial data, or another data-intensive industry.
Experience operating within a regulated environment and working with risk, compliance, audit, or regulatory stakeholders.
Demonstrated experience establishing enterprise data governance, stewardship, and data quality programs.
Experience with master data management, reference data, metadata management, taxonomy/ontology management, or data quality platforms.
Experience developing data operating models, standards, policies, and ownership frameworks.
Strong understanding of modern data platforms, integration patterns, data lineage, and data lifecycle management.
Experience evaluating and managing third-party data providers and data licensing relationships.
Experience identifying or developing opportunities to commercialize data products or proprietary datasets.
Demonstrated experience building or materially transforming an enterprise data-management capability.
Proven ability to build strong relationships with executives, analytical teams, product teams, engineers, customers, and external partners.
Ability to translate enterprise objectives into a clear, executable data strategy.
Excellent written and verbal communication skills, with the ability to tailor communication to senior executives, analytical professionals, regulators, and technical teams.

Nice To Haves

Experience preparing enterprise data for artificial intelligence, machine learning, semantic search, or other advanced analytical use cases is a plus.

Responsibilities

Define and execute KBRA's enterprise data management strategy and operating model.
Lead and develop the Data Operations organization, including data stewardship, master/reference data management, data quality, taxonomy, and related disciplines.
Manage day-to-day operational delivery, service levels, controls, escalation and capacity planning.
Establish standards for the organization, classification, definition, ownership, and lifecycle management of KBRA data.
Continue to mature KBRA’s data governance and data quality programs by establishing measurable standards for accuracy, completeness, consistency, timeliness, and exception management.
Establish and maintain an enterprise data-domain model, including data owners, stewards, authoritative sources, definitions, quality and lifecycle. Lead the development of taxonomies, ontologies, common definitions, and canonical data concepts across KBRA.
Partner with Engineering and Product on data architecture, data catalog/glossary development, metadata management, lineage, integration standards, and platforms supporting enterprise data management.
Ensure ratings-related data management processes, controls, lineage, and documentation meet applicable regulatory and audit expectations.
Serve as a senior point of contact for regulators, auditors, and other stakeholders on matters related to ratings data management and operations.
Partner with business leaders to identify, evaluate, and develop opportunities to commercialize KBRA's proprietary data assets.
Identify, evaluate, and onboard third-party data providers that improve the quality, coverage, efficiency, or automation of KBRA's data processes.
Evaluate and implement technology that automates and augments data ingestion, curation, matching, enrichment, stewardship, and quality management.
Establish KPIs and operating metrics for data quality, operational performance, stewardship, and data-management effectiveness.
Ensure KBRA's data assets are discoverable, well-defined, governed, traceable, and of sufficient quality to support artificial intelligence, machine learning, semantic search, advanced analytics, and other emerging data-driven capabilities.
Recruit, develop, and retain a high-performing data management organization capable of scaling with KBRA's growth.
Participate as a member of the Technology Leadership Team and contribute to KBRA's broader technology, product, and data strategy.
Establish and oversee change governance for critical data definitions, taxonomies, reference data, identifiers, and business rules, including impact assessment, review, approval, documentation, and communication of changes.
Lead data-governance forums and cross-functional data decisions/escalations.