Managing Director, Enterprise Data Governance & Data Operations

The Head of Enterprise Data Governance & Data Operations is responsible for ensuring the enterprise's data is trusted, usable, connected, and AI-ready. This role leads the evolution from fragmented, slow-moving data practices to scalable, decision-ready data assets that power analytics, AI, and agentic capabilities across the organization.

This leader owns the operating fabric around data including governance, standards, stewardship enablement, metadata, quality, access, and lifecycle management while accelerating the organization's ability to leverage data quickly and responsibly to drive informed decisions and innovation.

The role partners closely with business leaders, technology teams, analytics, AI product teams, legal/compliance, and security to ensure data governance is an enabler of speed and value, not a bottleneck., Enterprise Data Governance Leadership

• Continue to evolve the enterprise data governance strategy, aligning accountability, standards, and policies across business and technology teams.
• Establish clear decision rights for data ownership, stewardship, and usage-balancing compliance with business agility.
• Ensure governance supports AI, advanced analytics, and agentic use cases, including model-ready data, lineage, and ethical use considerations.
• Partner with Legal, Privacy, Risk, and Security to embed regulatory and ethical requirements into scalable, repeatable data practices.

Data Operations & Enablement

• Lead the development of a modern Data Operations function that enables faster data discovery, access, quality management, and lifecycle control.
• Build and manage enterprise capabilities such as metadata management, data quality monitoring, issue resolution workflows, and data observability.
• Reduce friction for analytics, product, and AI teams by standardizing intake, prioritization, and operational support for data needs.
• Enable data reuse and interoperability across domains to support connected data and enterprise-wide insights.
• Drive data integration and standards alignment across business units with distinct operating models, ensuring shared data assets serve enterprise-wide priorities while respecting business-specific needs.
• Support data licensing and external analytics use cases by ensuring enterprise data assets are designed as analytics- and AI-ready data products, with clear semantics, provenance, quality standards, and governance controls that enable safe reuse beyond internal reporting.

AI & Agentic Readiness

• Ensure enterprise data is AI-ready: well-described, governed, trusted, and accessible at scale.
• Support agentic systems by enabling data traceability, explainability, and appropriate guardrails for automated decision-making.
• Partner with AI and technology leaders to anticipate future data requirements and embed governance early in development lifecycles.

Business Partnership & Change Leadership

• Act as a trusted partner to business leaders helping them understand what data exists, how it can be used, and what is required to use it responsibly.
• Translate complex data concepts into clear, business-relevant outcomes.
• Drive cultural change so data governance is viewed as shared accountability and a business enabler.

Success Measures

• Increased speed and ease of data access for analytics, AI, and decision-making.
• Improved data trust, quality, and reuse across business domains.
• Clear, adopted ownership and stewardship models that scale beyond individual expertise.
• Reduced time-to-value for AI and advanced analytics use cases.
• Priority data domains reach AI-ready status within defined timelines.
• Track record of making data operationally usable for ML/AI at scale, not just governed in theory and experience with healthcare, insurance, or similarly regulated industries.
• Governance practices that are embedded in workflows, not enforced after the fact.

• Senior leadership experience in data governance, data operations, analytics enablement, or enterprise data management.
• Demonstrated ability to balance control with agility in complex, regulated environments.
• Deep understanding of how data powers AI, analytics, and digital products.
• Strong influence and communication skills across executive, business, and technical audiences.
• Proven ability to design and scale operating models, not just frameworks.

What This Role Is Not

• Not a compliance-only or policy-only role
• Not a data engineering or software development role
• Not focused on reporting or BI delivery

Doing something meaningful starts with a simple decision, a commitment to changing lives. At The Cigna Group, we're dedicated to improving the health and vitality of those we serve. Through our divisions Cigna Healthcare and Evernorth Health Services, we are committed to enhancing the lives of our clients, customers and patients. Join us in driving growth and improving lives., The Cigna Group has a tobacco-free policy and reserves the right not to hire tobacco/nicotine users in states where that is legally permissible. Candidates in such states who use tobacco/nicotine will not be considered for employment unless they enter a qualifying smoking cessation program prior to the start of their employment. These states include: Alabama, Alaska, Arizona, Arkansas, Delaware, Florida, Georgia, Hawaii, Idaho, Iowa, Kansas, Maryland, Massachusetts, Michigan, Nebraska, Ohio, Pennsylvania, Texas, Utah, Vermont, and Washington State. Qualified applicants with criminal histories will be considered for employment in a manner consistent with all federal, state and local ordinances.