Imagine being part of a team that is actively driving the future. At Davies, we combine technology, analytics, AI, and professional services to help clients solve complex business challenges across insurance and regulated industries. We are seeking a Lead Data Management & Governance Manager to establish and mature enterprise data governance, metadata management, data quality, and model risk management capabilities. This role will lead governance initiatives leveraging Microsoft Purview while partnering with Data Science, Data Engineering, Risk, Compliance, and business stakeholders to ensure trusted data and responsible AI practices across the organization. Key Responsibilities Lead enterprise data governance programs including data ownership, stewardship, quality, lineage, cataloging, and policy management. Design and implement governance frameworks using Microsoft Purview including data catalog, lineage, classification, and data estate management capabilities. Establish data quality standards, controls, monitoring, and remediation processes across critical business domains. Develop and maintain data governance policies, standards, and operating procedures. Lead machine learning model risk management initiatives including model inventory, validation, monitoring, explainability, and governance controls. Partner with Data Science and AI teams to ensure compliance with responsible AI and regulatory requirements. Drive metadata management, business glossary development, and data stewardship programs. Provide governance reporting and metrics to executive leadership and risk committees. Collaborate with security, compliance, legal, and business teams to align governance practices with organizational objectives. Skills, Knowledge and Expertise Bachelor's degree in Information Management, Computer Science, Data Analytics, Business, or related discipline. 7+ years of experience in data governance, data management, data quality, risk management, or related disciplines. Strong hands-on experience with Microsoft Purview and enterprise metadata management platforms. Experience implementing data governance frameworks, stewardship programs, and data quality initiatives. Knowledge of machine learning lifecycle management, model governance, model validation, and model risk controls. Strong understanding of regulatory, privacy, and compliance requirements impacting data and AI programs. Experience with SQL, analytics platforms, and modern cloud data ecosystems including Microsoft Fabric. Excellent stakeholder management, communication, and leadership capabilities. Strong analytical, organizational, and problem-solving skills.
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