Data Cloud Governance Manager

Job Title: Data Cloud Governance Manager
Location: East Hanover, NJ
Duration: 12 months
Hybrid: 3 days onsite, 2 days remote

Job Description:

• Client is on a mission to transform medicine and improve lives worldwide.
• As a global leader in healthcare, we leverage advanced technology and data to deliver patient-centric solutions, enhance customer engagement, and drive innovation.
• We collaborate closely with the US business, bringing insights and challenging ideas to empower smarter, data-driven decision-making.
• The US CRM organization sits within Strategy, Platforms & Transformation (SPT) AI & Platform Products and plays a crucial role in driving the transformation to a next-generation Customer360 operating model.
• Client seeks an accomplished product leader with a track record of turning business demand from multiple commercial functions into a well-managed data product backlog.
• Strong prioritization judgment, stakeholder partnership, and hands-on data fluency are essential to success in this role.
• Reporting to Director, PO Audience Activation & Marketing Intelligence, Data Cloud Governance Lead owns the enterprise governance framework for shared Data Cloud capabilities, ensuring that access, data protection, security, privacy, tagging, masking, and cross-boundary data sharing are designed and operated consistently.
• The role translates enterprise policies and regulatory expectations into actionable platform guardrails, partners with the IT Center of Excellence and architecture teams, and enables responsible delivery across Data Spaces without creating unnecessary friction.

Major Accountabilities:

• Govern enterprise policies: Own and evolve central attribute-based access control policies, tagging standards, dynamic masking rules, encryption expectations, and cross-space data-sharing guardrails.
• Manage governance intake: Receive and qualify requests for new access policies, tags, privacy controls, compliance rules, and exceptions; document scope, rationale, risk, and decision requirements.
• Assess risk and compliance: Evaluate proposed Data Streams, Data Lake Objects, integrations, and use cases for privacy, security, data protection, and regulated-data considerations, including PHI and PII where applicable.
• Translate policy into backlog: Convert governance needs into clear epics, features, policy updates, acceptance criteria, and implementation plans for platform and engineering teams.
• Support prioritization and backlog planning: Prioritize enterprise governance work based on risk, strategic value, dependencies, and platform capacity; maintain a transparent governance backlog and decision log.
• Provide PI planning assurance: Validate compliance and complete security reviews for new Data Streams, shared Data Lake Objects, and related enterprise capabilities before committed delivery.
• Lead control design and validation: Partner with IT, architecture, privacy, legal, security, and engineering teams to design practical controls and verify that controls are implemented as intended.
• Audit and monitor compliance: Establish evidence-based reviews of platform configurations, access, encryption, masking, tagging, and cross-boundary sharing; drive remediation of identified gaps.
• Enable scalable self-service: Publish reusable standards, decision criteria, templates, and guidance that allow Data Space teams to design compliant solutions earlier in the lifecycle.
• Communicate governance decisions: Explain policy intent, trade-offs, approvals, conditions, and exceptions clearly to business and technical stakeholders.

Key Performance Indicators:

• KPI area What good looks like
• Control effectiveness Governance controls are implemented, testable, and operating as designed.
• Review timeliness Security, privacy, and compliance reviews support planning and release decisions without avoidable delays.
• Policy coverage Shared Data Cloud capabilities are covered by current access, tagging, masking, encryption, and sharing standards.
• Audit and remediation Findings, exceptions, and remediation actions are documented, owned, and closed transparently.
• Decision quality Governance decisions are consistent, risk-based, traceable, and clearly communicated.
• Stakeholder adoption Data Space and delivery teams use governance guidance early and report clear, actionable support.

Ideal Background:

• Bachelor's degree in data, technology, business, engineering, computer science, or a related field required; advanced degree preferred.
• Fluent English; other languages are desirable.
• 5+ years of experience in data governance, privacy, security, risk, compliance, product management, or platform governance roles.
• Strong understanding of enterprise data controls, including access management, classification and tagging, masking, encryption, consent, retention, and controlled data sharing.
• Experience translating policy and regulatory requirements into platform standards, technical requirements, and delivery acceptance criteria.
• Demonstrated success working across business, IT, architecture, security, privacy, legal, data engineering, and product teams in a matrixed environment.
• Strong written and verbal communication skills, with the ability to explain complex control requirements to both technical and business audiences.
• Preferred
• Hands-on familiarity with Client Data Cloud governance capabilities, data models, Data Streams, Data Lake Objects, and platform access patterns.
• Experience in pharma, life sciences, healthcare, or another regulated and data-intensive industry.
• Knowledge of agile product delivery, risk-based controls, audit evidence, and enterprise architecture governance.
• Leadership Competencies

Navigate complexity

• Enable impactful and timely decision-making across business, data, technology, privacy, and compliance stakeholders.

• Identify the critical issues in complex situations, maintain focus on enterprise outcomes, and adapt priorities as conditions change.
• Take a long-term view of platform sustainability, downstream impacts, and reusable enterprise capabilities.

• Deliver collective impact
• Integrate diverse perspectives to achieve the best outcome for the enterprise.
• Influence without authority and collaborate effectively across organizational boundaries.
• Challenge assumptions constructively and make decisions grounded in evidence.