Head of Data Management - Managing Director (NY)

We need to output HTML fragment with sections using

for headings: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. Only include sections that have real specific content. We need to extract content from posting. We have: - About The Job (maybe corresponds to About the role). We'll use

About the role

and then prose. - Responsibilities: "What You'll Do" list of duties. Use

• . - Requirements/Qualifications/Skills: The "About You" section includes qualifications, experience, skills. We need to decide how to split. The instruction: Use headings for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). We can include multiple of these if content exists. We have qualifications (education, years experience), skills (communication, etc). Could combine Requirements and Qualifications? Better to separate: Requirements (maybe core requirements) and Qualifications (maybe education/experience) and Skills (soft skills). But we need to avoid filler. Let's parse. From posting: About You bullet points (actually paragraphs): "You are an entrepreneurial and pragmatic leader who views data as both an operational capability and a strategic business asset. You can establish a long-term vision while also working through complex implementation details. You are comfortable operating across business, analytical, product, engineering, and regulatory stakeholders and can translate between those audiences. You are an effective communicator who can clearly articulate a data strategy, build organizational alignment around it, and lead teams through significant change. You Will Be Successful in This Role If You Have: 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. Experience preparing enterprise data for artificial intelligence, machine learning, semantic search, or other advanced analytical use cases is a plus." Thus we have qualifications (education, years experience) and skills (communication, leadership, etc). We could put Requirements as the list of mandatory qualifications (education, years experience, leadership experience, industry experience, regulated environment, etc). Qualifications could be the "demonstrated experience establishing enterprise data governance..." etc. Skills could be communication, relationship building, etc. But we need to avoid duplication. Simplify: Use Requirements for the bullet list starting with "Bachelor's or master's degree..." etc (the hard requirements). Use Qualifications for the list of demonstrated experience items (data governance, MDM, etc). Use Skills for the communication/relationship building items. But we need to ensure we don't create sections with placeholder text. All have content. Benefits: we have bullet list: "A hybrid work schedule (Tuesday, Wednesday, Thursday in the office) Competitive benefits and paid time off Paid family and disability leave 401(k) plan, including employer match (100% vested) Educational and professional development financial assistance Employee referral bonus program". We'll format as
  • . Pay: Salary Range: "$225,000 to $300,000". We'll put

    . Schedule: hybrid work schedule already in benefits; but schedule could be separate? The posting mentions hybrid schedule under Benefits. We could still have a Schedule section if we want, but it's duplicate. Better to not create Schedule section if it's just same as benefits; but we have benefits already includes schedule. The instruction: only include a section when posting has real, specific content for it. Since schedule is mentioned as part of benefits, we could still include Schedule section with that detail, but it's duplicate. Safer to omit Schedule and keep schedule inside Benefits. Thus sections: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay. Now we need to preserve all substantive information, not invent or summarize away detail. We need to include all details from each section. Let's extract About the role content: The paragraph(s) under "About The Job". It includes multiple sentences. We'll combine into

    maybe multiple

    but we can put all in one

    . Ensure we keep all details. About The Job text: "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." Note there are missing spaces after periods; we should preserve as is? Probably we should keep the text but we can add spaces for readability? The instruction: preserve ALL substantive information; do not invent or summarize away detail. Adding spaces is not changing substantive info, just formatting. It's okay. We'll output as

    with the text. Responsibilities: "What You'll Do" list. We'll extract each line as

  • . Ensure we keep all. List items: - 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. We'll put each as
  • . Requirements: The list starting with "Bachelor's or master's degree or equivalent relevant experience." through "Experience operating within a regulated environment and working with risk, compliance, audit, or regulatory stakeholders." We'll include each as
  • . Let's list: - 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. Qualifications: The list of demonstrated experience items: - 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. - Experience preparing enterprise data for artificial intelligence, machine learning, semantic search, or other advanced analytical use cases is a plus. Note the last one says "is a plus." We'll keep. Skills: maybe we could treat communication and relationship building as skills, but we already included them in Qualifications. To avoid duplication, maybe we should not have Skills section; we could put those under Qualifications. But the instruction allows us to include Skills if we have content. However we risk duplication. Better to keep Qualifications as all the "You Will Be Successful..." list, and not create separate Skills. But we need to follow the heading list: we can include Skills if we have content; but we can also omit if we think it's redundant. The instruction: "Prefer a few substantive sections over many thin ones." So we could combine Qualifications and Skills into one section called Qualifications (or Requirements). But we already have Requirements separate. We could have Requirements (education, years experience, leadership, industry, regulated) and Qualifications (the rest). That seems fine. No Skills section needed. Thus sections: About the role, Responsibilities, Requirements, Qualifications, Benefits, Pay. Now Benefits: list items: - A hybrid work schedule (Tuesday, Wednesday, Thursday in the office) - Competitive benefits and paid time off - Paid family and disability leave - 401(k) plan, including employer match (100% vested) - Educational and professional development financial assistance - Employee referral bonus program Pay: Salary Range: "$225,000 to $300,000." Also note "Offer amounts are determined by factors such as experience, skills, geography, and other job-related factors." We'll include that as part of Pay section. Now produce HTML fragment. We'll wrap each section in

    heading then content. For About the role: