Data Cloud Governance Manager

Job Title:

Data Cloud Governance Manager

Location:

East Hanover, NJ Hybrid (3 days (Mon-Thurs), 2 remote)
Pay rate: ***/hour - ***/hour (Lowest would be better)

*** 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 Customer
360 operating model.

*** 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.

• 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.

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.

• 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…