About this role
We are seeking a principal-level (L7) leader to own and drive the Enterprise Data Strategy, AI, and New Datamart vision across our ERP-centric technology landscape. This role spans enterprise platforms including SAP S/4HANA, Oracle Cloud Applications and similar ERP ecosystems leveraging modern data platforms such as SAP Datasphere, Oracle Analytics Cloud, Databricks, Amazon Redshift, or equivalent to build a unified, intelligent data fabric. This leader will serve as the strategic bridge between enterprise data architecture, advanced analytics, and business intelligence — translating complex, multi-Enterprise application data landscapes into actionable, AI-powered insights at scale. The ideal candidate is platform-fluent but platform-agnostic, able to design data strategies that harness the best of any enterprise application ecosystem while maintaining a clean, governed, and extensible data foundation. A critical mandate of this role is to establish and chair a Data Governance Council within Manufacturing Operations, driving cross-functional alignment across Engineering, Manufacturing, Supply Chain, and Finance to ensure data integrity, standardization, and actionable intelligence throughout the manufacturing value chain. Key job responsibilities Enterprise 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 SAP Datasphere, 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 across disparate enterprise systems, enabling consistent metrics, KPIs, and definitions across all functional 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 initiatives regardless of the underlying ERP platform. • Architect cloud data warehousing, data marts, and data pipelines & orchestration to ensure 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 — with particular emphasis on Manufacturing Operations data standards. Manufacturing Operations Data Governance Council This role is accountable for chartering, establishing, and chairing a Data Governance Council within Manufacturing 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 its mission, 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), enforce data standards across shop-floor systems, and enable real-time manufacturing analytics. • Align with Supply Chain on demand planning data, inventory master data, logistics and fulfillment metrics, and end-to-end supply chain visibility through governed data pipelines. • Coordinate with Finance to ensure manufacturing cost data, variance analysis, standard costing, and COGS reporting are underpinned by trusted, governed data from operational systems. • Define and enforce cross-functional data standards, data ownership models, stewardship roles, 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 Embedded Analytics (Fiori), Oracle OTBI/BI Publisher, or equivalent built-in reporting tools. • Drive the evolution of Enterprise Analytics & BI leveraging platforms such as SAP Analytics Cloud (SAC), Oracle Analytics Cloud (OAC), Amazon QuickSight, Tableau, or Power BI for dashboards, 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 access and empower business users with self-service analytics capabilities across all ERP platforms. • Standardize operational reporting, ad-hoc reporting, and embedded analytics patterns that work 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 Applications leveraging 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 chain optimization, financial planning, anomaly detection, and process automation across ERP platforms. 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, and exception-based alerting through AI-powered workflows integrated with enterprise applications. • Establish AI governance frameworks ensuring responsible, compliant, and explainable AI across 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 core strategy, extension strategies (e.g., SAP BTP, Oracle Cloud Infrastructure, AWS), and integration standards. • Collaborate with integration teams for data orchestration across cloud and on-premises ERP systems — managing API gateways, event-driven architectures, and ETL/ELT pipelines. • Drive platform evolution toward modern data architectures such as SAP Business Data Cloud, Oracle Lakehouse, AWS Data Lake, Databricks Lakehouse — evaluating and road mapping the best-fit architecture for the enterprise. • Interface with Process & Business Excellence to translate business demand into data solutions, ensuring tight alignment between business requirements and data architecture decisions across all ERP systems.