Chief Data Officer

We need to output HTML fragment with sections: About the role? The posting includes overview, responsibilities, technical skills & requirements, expanded qualifications. We need headings: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. Only include sections that have real specific content. We have overview (could be About the role). Responsibilities section present. Technical Skills & Requirements could be Skills. Expanded Qualifications could be Qualifications. No explicit Benefits, Pay, Schedule. So we omit those. We must not repeat job title as heading. Use

for each section heading. We need to preserve all substantive information, no boilerplate. Remove EEO etc. Also remove "Job Description:" line? It's just a label; we can incorporate content. We need to format responsibilities as

• . Also technical skills and qualifications as lists. We need to keep location, reports to, department? Those are metadata; we can fold into a short

  maybe under About the role? The instruction: do NOT put Job ID/requisition numbers as headings — fold minor metadata into a short

  or drop it. So we can include location, reports to, department in a paragraph. We must not invent or summarize away detail. Keep all specifics. Let's extract content: Overview paragraph: "The Head of Chief Data Officer (CDO) is a transformative senior leadership role tasked with architecting, building, and scaling Starr’s global enterprise data platform, data organization, and strategy. This executive is responsible for delivering sophisticated data integration, master data management, governance, augmentation, and advanced analytics solutions tailored to support complex insurance business functions, including Actuarial, Underwriting, Claims, Compliance, and Finance—while enabling a unified, global view of enterprise-wide data assets. CDO leads the creation of a modern, comprehensive enterprise data ecosystem, championing technical innovation (cloud, medallion architecture, data augmentation, external data enrichment), robust governance, and seamless accessibility. Beyond platform leadership, the role is accountable for designing and building out a world-class data organization, encompassing core teams for architecture, engineering, analytics, governance, operations, and stewardship." We could keep that as About the role. Responsibilities list: The responsibilities section includes bullet-like sentences separated by periods. We need to parse into list items. Responsibilities text: "Enterprise Data Strategy & Platform Leadership Own and drive the global enterprise data strategy, aligning with business objectives, regulatory requirements, and future innovation.Architect and deliver a scalable, world-class multicloud /hybrid enterprise data platform, supporting complex insurance applications and analytics.Lead development and execution of platform onboarding, external data augmentation, and business adoption roadmaps. Data Organization Design & Team Leadership Build and structure a robust data organization spanning enterprise data architecture, engineering, governance, data operations, analytics enablement, and data stewardship.Recruit, mentor, and inspire high-performing global teams: data architects, engineers, ETL/ELT specialists, platform administrators, data governance and quality experts, data ops/operations, and metadata specialists.Establish clear lines of responsibility, career growth paths, and collaboration practices for each data function. Technical Solution Design & Data Ecosystem Development Lead design and engineering of complex batch and real-time pipelines using diverse ingestion patterns (CDC, APIs, files, streaming platforms).Implement Medallion architectures (bronze/silver/gold layers) leveraging Databricks, Fabric, and other leading cloud-based data platforms.Architect, deliver, and manage master data management (MDM) systems for key insurance entities (policies, customers, claims, products, finance).Develop a comprehensive data augmentation ecosystem to integrate external third-party data - e.g., catastrophe models, market feeds, regulatory databases, fraud/risk scoring, industry benchmarking - and combine/enrich internal datasets for holistic analysis and reporting. Data Governance, Stewardship, & Compliance Define, operationalize, and oversee enterprise-wide data governance policies for stewardship, quality, access, lineage, cataloging, and regulatory compliance (GDPR, CCPA, SOX, NAIC, etc.).Ensure rigorous data privacy, usage, and retention management across all data domains.Build teams responsible for ongoing governance operations, metadata management, and audit readiness. Stakeholder Engagement & Business Partnership Act as the chief liaison for all enterprise data initiatives, collaborating deeply with insurance business functions (Actuarial, Claims, Underwriting, Compliance, Finance, IT, and external partners).Facilitate business requirement gathering, educate stakeholders on data capabilities, and promote adoption and value realization from data platform investments. Operational Excellence, Innovation & Change Leadership Govern operational reliability, performance, security, scalability, monitoring, and automation of all data assets.Foster innovation through adoption of new technologies, best practices, and continuous improvement methods; empower agile, cross-functional working across data teams.Champion enterprise data literacy and a culture of high performance and transformation. Financial Stewardship & Resource Management Manage departmental budgets, resourcing, and vendor relationships for all data platform and organizational functions; drive value realization and cost optimization for data investments.Proactively manage risk, business continuity, and compliance for critical data assets and operations. KPIs & Continuous Improvement Define, monitor, and optimize critical metrics: pipeline reliability and latency, data quality, master data coverage and integrity, speed to market for integrations/augmentations, platform scalability and cost efficiency, regulatory compliance, and business user satisfaction." We need to split into list items. Probably each sentence after a period is a separate responsibility. Could group by headings but we just need list. We'll create

  • for each distinct responsibility sentence. Similarly Technical Skills & Requirements: list of bullet-like sentences separated by periods. Technical Skills & Requirements text: "Advanced hands-on experience: cloud-native data platforms (Databricks, Snowflake, AWS/Azure/GCP Data Services), Medallion architecture, batch/streaming pipelines, event-driven architectures, Spark, SQL, Python, Scala.Proven success implementing MDM solutions and integrating with operational and analytical warehouses, including external data sources.Deep experience in building ETL/ELT frameworks using diverse technologies and patterns for heterogeneous data sources.Mastery of metadata management and data cataloging tools (Collibra, Informatica, Azure Purview).Extensive knowledge of enterprise data governance, stewardship, lineage, residency and regulatory frameworks, audit and privacy (GDPR, CCPA, SOX, NAIC, etc.).Demonstrated expertise with insurance data models and the process flows of core functions (Actuarial, Claims, Underwriting, Compliance, Finance).Experience designing self-service and democratized data access environments." We'll split each sentence. Expanded Qualifications text: "Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, Information Systems, or related field; advanced degree highly preferred.15+ years of progressive enterprise data and analytics experience, including 5+ years leading large-scale, global data organizations in insurance (P&C and Specialty).Proven track record building, leading, and organizing data architecture, engineering, governance, and operations functions.Extensive success in integrating internal and external data assets, supporting AI/ML analytics, and delivering enterprise reporting systems for insurance organizations.Experience leading distributed (onshore/offshore/global) technical teams and managing complex vendor/partner relationships.Deep financial management and budgeting experience for large-scale data platform/organization operations.Outstanding leadership, transformation, and stakeholder management abilities.Certifications in data engineering, cloud platforms, MDM, or insurance data management (e.g., AWS, Azure, GCP Architect, Databricks Certified, AID, CPCU).Experience with core insurance, reinsurance, claims and financial platforms and their data architectures (Guidewire, Duck Creek, Majesco, SAP, Workday ERP solutions, etc.)." We'll split each sentence. Now we need to include location, reports to, department maybe in a paragraph under About the role. We'll produce:

    About the role

    Location: New York, New York. Reports to: Global CIO. Department: Starr Technology Group. The Head of Chief Data Officer (CDO) is a transformative senior leadership role tasked with architecting, building, and scaling Starr’s global enterprise data platform, data organization, and strategy. This executive is responsible for delivering sophisticated data integration, master data management, governance, augmentation, and advanced analytics solutions tailored to support complex insurance business functions, including Actuarial, Underwriting, Claims, Compliance, and Finance—while enabling a unified, global view of enterprise-wide data assets. CDO leads the creation of a modern, comprehensive enterprise data ecosystem, championing technical innovation (cloud, medallion architecture, data augmentation, external data enrichment), robust governance, and seamless accessibility. Beyond platform leadership, the role is accountable for designing and building out a world-class data organization, encompassing core teams for architecture, engineering, analytics, governance, operations, and stewardship.

    Then Responsibilities

    Responsibilities

    with each
    • . Then Skills

      Skills

      . Then Qualifications

      Qualifications

      . Make sure not to include empty sections. We must output only HTML fragment. Let's craft list items. Responsibilities sentences (split by period). Need to ensure each ends with a period inside
      • . We'll keep original phrasing. 1. Own and drive the global enterprise data strategy, aligning with business objectives, regulatory requirements, and future innovation. 2. Architect and deliver a scalable, world-class multicloud /hybrid enterprise data platform, supporting complex insurance applications and analytics. 3. Lead development and execution of platform onboarding, external data augmentation, and business adoption roadmaps. 4. Build and structure a robust data organization spanning enterprise data architecture, engineering, governance, data operations, analytics enablement, and data stewardship. 5. Recruit, mentor, and inspire high-performing global teams: data architects, engineers, ETL/ELT specialists, platform administrators, data governance and quality experts, data ops/operations, and metadata specialists. 6. Establish clear lines of responsibility, career growth paths, and collaboration practices for each data function. 7. Lead design and engineering of complex batch and real-time pipelines using diverse ingestion patterns (CDC, APIs, files, streaming platforms). 8. Implement Medallion architectures (bronze/silver/gold layers) leveraging Databricks, Fabric, and other leading cloud-based data platforms. 9. Architect, deliver, and manage master data management (MDM) systems for key insurance entities (policies, customers, claims, products, finance). 10. Develop a comprehensive data augmentation ecosystem to integrate external third-party data - e.g., catastrophe models, market feeds, regulatory databases, fraud/risk scoring, industry benchmarking - and combine/enrich internal datasets for holistic analysis and reporting. 11. Define, operationalize, and oversee enterprise-wide data governance policies for stewardship, quality, access, lineage, cataloging, and regulatory compliance (GDPR, CCPA, SOX, NAIC, etc.). 12. Ensure rigorous data privacy, usage, and retention management across all data domains. 13. Build teams responsible for ongoing governance operations, metadata management, and audit readiness. 14. Act as the chief liaison for all enterprise data initiatives, collaborating deeply with insurance business functions (Actuarial, Claims, Underwriting, Compliance, Finance, IT, and external partners). 15. Facilitate business requirement gathering, educate stakeholders on data capabilities, and promote adoption and value realization from data platform investments. 16. Govern operational reliability, performance, security, scalability, monitoring, and automation of all data assets. 17. Foster innovation through adoption of new technologies, best practices, and continuous improvement methods; empower agile, cross-functional working across data teams. 18. Champion enterprise data literacy and a culture of high performance and transformation. 19. Manage departmental budgets, resourcing, and vendor relationships for all data platform and organizational functions; drive value realization and cost optimization for data investments. 20. Proactively manage risk, business continuity, and compliance for critical data assets and operations. 21. Define, monitor, and optimize critical metrics: pipeline reliability and latency, data quality, master data coverage and integrity, speed to market for integrations/augmentations, platform scalability and cost