Data Governance Lead

Need exp from F50 - like META, AMAZON, Apple, Adobe. Etc, 1. Trusted Data Foundation

o Design, implement, and govern the enterprise trusted data foundation within Databricks, including Gold-layer data models, data quality controls, curated metrics views, and Unity Catalog lineage management.

1. KPI Taxonomy & Performance Data Modeling

o Own and maintain the KPI taxonomy, establishing clear relationships between executive-level metrics, operational drivers, and root-cause indicators.

o Develop and govern the enterprise performance data model, providing standardized definitions, time grains, dimensional hierarchies, and reporting structures across all supply chain domains.

1. Master Data Governance

o Lead master data governance initiatives across product, supplier, customer, and compliance domains.

o Establish standards, policies, and governance processes that improve data consistency, quality, and AI-enabled attribute discovery capabilities.

1. Metric Certification & Standardization

o Define metric certification requirements and governance procedures for inclusion in official reporting.

o Develop standardized KPI calculation frameworks, including actuals versus targets, rolling averages, period-over-period comparisons, and statistical process control methodologies.

o Establish target and threshold management processes that support cascading business objectives, seasonal adjustments, and planning updates.

1. AI Readiness & Cross-Functional Data Governance

o Lead enterprise Data Readiness for AI initiatives by developing assessment frameworks that evaluate completeness, accuracy, governance maturity, and automation readiness.

o Enable natural language access to certified metrics through platforms such as ThoughtSpot, AtScale, Power BI, Looker, Tableau, or similar technologies.

o Drive alignment on metric definitions, reporting standards, and measurement methodologies across business and technology teams.

o Serve as a data governance subject matter expert in architecture reviews and mentor analysts, data engineers, and BI developers to promote sustainable governance practices.

• Strong background in Data Governance, Data Management, or Data Architecture.

• Experience with Databricks, Unity Catalog, data lineage, and enterprise data platforms.

• Expertise in KPI framework design, metric governance, and data modeling.

• Experience establishing master data governance programs and enterprise data standards.

• Knowledge of AI/ML data readiness, data quality assessment frameworks, and analytics platforms.

• Ability to influence cross-functional stakeholders in a matrixed environment without direct authority.

• Strong communication, leadership, and mentoring skills.