Position OverviewWe are seeking an execution-focused
Program Manager for Data and AI to lead the digital transformation of our hybrid global supply chain network. In this role, you will bridge the gap between legacy operations, our modern SAP S/4HANA digital core, and advanced data science. You will orchestrate cross-functional teams to build scalable machine learning models and intelligent automation that consume and harmonize data across a fragmented ERP landscape. Your work will directly unlock the power of multi-system data to optimize inventory, embed predictive forecasting, and drive autonomous decision-making across our end-to-end supply chain.
Department: Information Technology / Data Science / Innovation
- Reports To: Director of Data, Analytics and Development
- Employment Type: Full-time or Contract to Hire
- Location: On-Site
Key ResponsibilitiesMulti-ERP AI Strategy & Program Execution- Lead the end-to-end delivery roadmap for AI, machine learning, and advanced analytics initiatives across a hybrid ecosystem of modern SAP S/4HANA and legacy ERP systems
- Manage schedules, milestones, dependencies, and resources for embedding intelligent technologies (e.g., SAP Business AI, custom cloud ML models) into diverse logistics and manufacturing workflows.
- Orchestrate the deployment of predictive and generative AI models that harmonize data across fragmented systems to transform reactive workflows into unified, predictive operations.
- Define and track program governance, agile delivery standards, and business ROI metrics for all data and AI deployments.
Data Harmonization & Integration Governance- Oversee the architectural orchestration of massive data volumes extracted from siloed legacy databases and SAP S/4HANA into unified cloud data platforms (e.g., SAP Datasphere, Snowflake, Databricks, AWS, or Azure).
- Partner with data engineering teams to establish robust data cleansing, mapping, and harmonization pipelines, ensuring clean master data (materials, vendors, customers) across mismatched ERP platforms for AI model training.
- Coordinate data extraction and ETL workflows across standard modules (e.g., SAP S/4HANA MM/SD/PP, legacy WMS, legacy TMS, and external IoT feeds).
- Ensure hybrid data handling workflows comply with international logistics regulations, enterprise security policies, and global data privacy laws.
Stakeholder Alignment & Change Management- Serve as the central communication hub between executive supply chain leadership, legacy system technical teams, SAP functional analysts, and data science groups.
- Translate highly complex data mapping, algorithmic methodologies, and hybrid architectural strategies into clear, value-driven business narratives for executive leadership.
- Drive comprehensive change management and user-adoption frameworks to ensure plant, warehouse, and purchasing managers trust and adopt AI-driven recommendations despite underlying data fragmentation.
Technical Skills- ERP Landscape Expertise: Strong functional or technical familiarity with SAP S/4HANA core supply chain modules (MM, SD, PP) alongside an understanding of legacy transactional tables and relational databases.
- Data Integration & Harmonization: Working knowledge of middleware, ETL/ELT pipelines, API frameworks, and cloud data ecosystems used to merge disparate data streams.
- AI & Machine Learning: Foundational understanding of the machine learning lifecycle, predictive modeling, demand forecasting algorithms, or generative AI extensions for automated procurement and sourcing.
- Methodologies: Expert mastery of Agile, Scrum, and SAP Activate or hybrid project deployment methodologies alongside delivery applications like Jira or Azure DevOps.
