More jobs:
AVP, Data Governance - Hybrid; Jersey
Job in
Jersey City, Hudson County, New Jersey, 07390, USA
Listed on 2026-10-05
Listing for:
McNeil & Co.
Full Time
position Listed on 2026-10-05
Job specializations:
-
IT/Tech
Information & Knowledge Management
Job Description & How to Apply Below
- a clear training and enablement strategy (plan, materials, and delivery approach) engagement and learning cadence, including forums and structured training touchpoints proficiency standards, learning progression, and measurable outcomes
- Drive steward execution and consistency through direct engagement, facilitation, and follow‑through, reinforcing clear expectations and accountability for delivery.
- Support reinforcement of Data Owner accountability through preparation, facilitation, and intervention, partnering with the SVP for direct engagement when senior‑level alignment or decision authority is required, and engaging more independently as experience and trust are established.
- Continuously evolve the stewardship model, including onboarding and ongoing training plans, based on feedback, delivery signals, and changes in business or governance priorities.
- Ensure the Data Stewardship Program explicitly supports analytics and AI use cases by defining stewardship expectations for AI‑relevant data sets, including data quality, lineage transparency, business context, and ongoing accountability.
Accountable for defining, enforcing, and sustaining minimum data catalog completeness standards for critical data assets, including ownership, business definitions, classifications, lineage, and usage context. Ensure the completeness, accuracy, consistency, and ongoing maintenance of the enterprise data catalog to support reuse, single‑point definitions, and trustworthy analytics and AI outcomes. Promote and reinforce active use of the data catalog as an operational governance tool for decision‑making, data quality management, reuse, transparency, and regulatory readiness—not merely as documentation.
Apply a trust‑but‑verify approach by validating assumptions, logic, and proposed approaches before scaling standards or practices; apply a working understanding of data quality, privacy, and analytics/AI dependencies to identify downstream impacts and engage appropriate accountable owners early. Ensure data catalog gaps (e.g., missing, unclear, or stale metadata or lineage) are explicitly tracked, assigned, and driven to closure as part of stewardship, domain, or initiative execution.
Partner with data stewards, data, technology, and analytics teams, as well as supporting data team members, to translate governance intent into executable outcomes while maintaining clear ownership boundaries.
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