Required Skills: Data Governance, Data Management, Data Architecture, Enterprise data platforms, Enterprise data standards, Data quality governance, Data lineage, Databricks, Unity Catalog, Gold-layer data models, Lineage management, Trusted data foundation, KPI, Performance Data, KPI taxonomy, KPI framework design, Metric governance, Performance data modeling, Natural-language access to certified metrics, Analytics, BI Platforms Mentioned, ThoughtSpot, AtScale, Power BI, Looker, Tableau
Job Description
Key Responsibilities
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.
2.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.
3.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.
4.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.
5.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.
Required Skills & Experience
• 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.