Principal, Enterprise Data Strategy, AI & Analytics, Amazon Leo

We are seeking a principal-level (L7) leader to own and drive the Enterprise Data Strategy, AI, andNew Datamart vision across our ERP-centric technology landscape. This role spans enterpriseplatforms including SAP S/4HANA, Oracle Cloud Applications and similar ERP ecosystems leveragingmodern data platforms such as SAP Datasphere, Oracle Analytics Cloud, Databricks, AmazonRedshift, or equivalent to build a unified, intelligent data fabric.This leader will serve as the strategic bridge between enterprise data architecture, advancedanalytics, and business intelligence — translating complex, multi-Enterprise application datalandscapes into actionable, AI-powered insights at scale. The ideal candidate is platform-fluent butplatform-agnostic, able to design data strategies that harness the best of any enterprise applicationecosystem while maintaining a clean, governed, and extensible data foundation.A critical mandate of this role is to establish and chair a Data Governance Council withinManufacturing Operations, driving cross-functional alignment across Engineering, Manufacturing,Supply Chain, and Finance to ensure data integrity, standardization, and actionable intelligencethroughout the manufacturing value chain.Key job responsibilitiesEnterprise Data Strategy & Datamart Architecture• Define and own the enterprise data strategy across ERP-centric environments (SAP, Oracle,or similar), establishing the roadmap for modernizing legacy data warehouses into cloud-native datamarts.• Design and implement a new Datamart architecture leveraging platforms such as SAPDatasphere, Amazon Redshift, Aurora, unifying ERP and non-ERP data through virtualization,replication, or hybrid approaches.• Establish the semantic layer and business data fabric that preserves business context acrossdisparate enterprise systems, enabling consistent metrics, KPIs, and definitions across allfunctional domains (Finance, Supply Chain, Manufacturing, Engineering, Order-to-Cash,Procurement).• Lead Data Modeling & Semantic Layer design — defining reusable business terms, metrics,relationships, and associations that support analytics, planning, and AI/ML initiativesregardless of the underlying ERP platform.• Architect cloud data warehousing, data marts, and data pipelines & orchestration toensure scalable, performant, and governed data delivery from multiple ERP sources.Own Data Quality & Governance frameworks ensuring data integrity, lineage, certification,and lifecycle management across all enterprise datamarts and ERP systems — withparticular emphasis on Manufacturing Operations data standards.Manufacturing Operations Data Governance CouncilThis role is accountable for chartering, establishing, and chairing a Data Governance Council withinManufacturing Operations. The council will drive cross-functional data alignment and decision-making across key operational domains:• Charter and launch the Manufacturing Operations Data Governance Council, defining itsmission, scope, membership, decision rights, escalation paths, and cadence of reviews.• Collaborate with Engineering to standardize product data definitions, BOM structures,engineering change order data flows, and design-to-manufacturing data handoffs.• Partner with Manufacturing to govern production data (MES, quality, yield, OEE), enforcedata standards across shop-floor systems, and enable real-time manufacturing analytics.• Align with Supply Chain on demand planning data, inventory master data, logistics andfulfillment metrics, and end-to-end supply chain visibility through governed data pipelines.• Coordinate with Finance to ensure manufacturing cost data, variance analysis, standardcosting, and COGS reporting are underpinned by trusted, governed data from operationalsystems.• Define and enforce cross-functional data standards, data ownership models, stewardshiproles, and data quality SLAs across all council-participating functions.• Establish a data issue resolution framework with clear escalation paths and accountability,ensuring disputes over data definitions, ownership, and quality are resolved efficiently.• Report governance health metrics to senior leadership, including data quality scorecards,policy compliance rates, and council effectiveness KPIs.Enterprise Reporting & Analytics• Set the strategic direction for ERP-native reporting capabilities — including SAP EmbeddedAnalytics (Fiori), Oracle OTBI/BI Publisher, or equivalent built-in reporting tools.• Drive the evolution of Enterprise Analytics & BI leveraging platforms such as SAP AnalyticsCloud (SAC), Oracle Analytics Cloud (OAC), Amazon QuickSight, Tableau, or Power BI fordashboards, scorecards, planning, predictive analytics, and self-service analytics.• Define and implement KPI Frameworks and Data Visualization standards, enabling insight-to-action workflows across the enterprise independent of the source ERP system.• Champion User Enablement & Adoption designing programs that democratize data accessand empower business users with self-service analytics capabilities across all ERP platforms.• Standardize operational reporting, ad-hoc reporting, and embedded analytics patterns thatwork consistently whether the source system is SAP, Oracle, or a third-party <application.AI> & Advanced Analytics• Identify, prioritize, and deliver Generative AI Use Cases for Enterprise Applicationsleveraging AI services (e.g., Amazon Bedrock, Amazon Q, SAP Joule, Oracle AI, Azure OpenAI)to embed intelligence into ERP-driven business processes.• Build and scale Machine Learning Models for demand forecasting, supply chainoptimization, financial planning, anomaly detection, and process automation across <ERPplatforms.Drive> Forecasting & Optimization initiatives that convert historical ERP data (from SAP,Oracle, or similar) into predictive and prescriptive insights.• Lead Intelligent Automation efforts automating repetitive data tasks, report generation, andexception-based alerting through AI-powered workflows integrated with enterpriseapplications.• Establish AI governance frameworks ensuring responsible, compliant, and explainable AIacross all analytics use cases, regardless of the underlying ERP or data platform.Integration & Platform Evolution• Partner with Architecture & Governance teams to ensure alignment with clean corestrategy, extension strategies (e.g., SAP BTP, Oracle Cloud Infrastructure, AWS), andintegration standards.• Collaborate with integration teams for data orchestration across cloud and on-premises ERPsystems — managing API gateways, event-driven architectures, and ETL/ELT pipelines.• Drive platform evolution toward modern data architectures such as SAP Business DataCloud, Oracle Lakehouse, AWS Data Lake, Databricks Lakehouse — evaluating and roadmapping the best-fit architecture for the enterprise.• Interface with Process & Business Excellence to translate business demand into datasolutions, ensuring tight alignment between business requirements and data architecturedecisions across all ERP systems.