AD, Data Governance Lead

Novartis•East Hanover, NJ

35d•$145,600 - $270,400•Onsite

About The Position

The AD, Data Governance Lead is accountable for designing, standing up, and operating the enterprise data governance program. This individual establishes the governance operating model- including the Executive Council and core functional sub-committees- defines data lifecycle controls, builds performance scorecards, and partners cross-functionally with IT, Compliance, Legal, and Privacy to embed sustainable, auditable data controls across the organization.

Requirements

Bachelor's degree in Business Administration, Information Systems, Data Management, Engineering, Finance, or a related field.
Strong facilitation and stakeholder-management skills — this role lives in meetings with functional VPs.
Minimum 8+ years in Data governance, BI governance, or commercial analytics in a regulated industry. Preferably in pharma or life sciences industries.
Extensive Experience running a cross-functional governance council or working group with real decision authority.
Influence without authority across IT, Legal, Compliance, and Privacy.
Deep knowledge of governance frameworks (DAMA-DMBOK, DCAM), privacy regulations, and control design.
Experience with governance/catalog tooling (e.g., OpenMetadata, Collibra).
Analytical rigor for scorecard/metric design and maturity assessment.

Nice To Haves

Pharma or life sciences industries experience.

Responsibilities

Stand up and co-chair the Executive Council and coordinate all sub-committees.
Develop charters, terms of reference, meeting cadences, agendas, and decision-tracking.
Drive alignment of governance priorities with enterprise strategy and risk appetite.
Establish federated data ownership and stewardship model across domains.
Partner with IT, Compliance, Legal, and Privacy to fully develop, validate, and operationalize required controls.
Develop, document, and maintain control frameworks at each lifecycle stage.
Collaborate with data owners and enforce governance standards across the end-to-end data lifecycle.
Build Data Management Lifecycle Scorecards measuring quality, coverage, compliance, and maturity.
Define Governance KPIs/KRIs (e.g., data quality scores, classification coverage %, access-review completion, issue MTTR, policy adoption).
Deliver executive dashboards and periodic DCAM maturity assessments.