GP KPIs, Metrics & Program Reporting Support GP KPI frameworks by ensuring metric definitions, data sources, and calculations are clearly defined, standardized, and auditable. Enable consistent, trusted program and transformation reporting by improving data reliability and transparency. Partner with GP program owners to align reporting needs with governed data sources and approved definitions. Execute day-to-day procurement data governance activities, including stewardship support, data quality monitoring, issue intake, and remediation tracking. Support the procurement data stewardship operating model, including routines, escalation paths, and documentation. Perform hands-on procurement master data cleanup and standardization activities (supplier, category, material, contract, and reference data). Coordinate with Master Data and process owners to resolve data quality issues at the source and prevent recurrence. Support continuous improvement of master data processes and controls. Contribute to procurement master data strategy required to enable AI, automation, and advanced analytics use cases. Ensure procurement data is structured, labeled, and governed to be AI ready, with clear ownership, definitions, and quality thresholds. Act as a liaison between GP business teams, Analytics, AI, Master Data, and IT for data related topics. Support alignment between procurement specific needs and enterprise data governance standards. Bachelor's degree in computer science, Information Systems, Data Analytics, or related field required. Advanced degree or certification in data management, analytics, or governance is a plus. Practical experience with cloud data platforms (e.g., Snowflake) is required. 3-4 years of experience in data governance, data quality, analytics, or reporting roles. Hands-on experience with master data management and data quality operations, preferably in Procurement or Supply Chain domains. Basic knowledge of any Business Intelligence tools for Reporting such as Tableau/ Power BI is a plus Experience supporting KPI frameworks, metrics definition, and program reporting. Exposure to AI, advanced analytics, or data readiness initiatives is strongly preferred. Strong analytical mindset with high attention to detail and data accuracy. Working knowledge of data governance concepts including stewardship, ownership, critical data elements, and quality metrics. Ability to translate business questions into clear data definitions and measurable metrics. Comfortable working cross-functionally and influencing without direct authority. Clear communicator with the ability to document standards, definitions, and processes. Understanding how data quality and standardization enable automation, analytics, and AI outcomes.
