Deskripsi Pekerjaan
Required Qualifications : Education Bachelor's degree in Computer Science, Information Systems, Engineering, or related field. Master's (MBA or MIT) is a plus. Experience 10+ years in IT, with at least 5–7 years in senior IT leadership (Head of IT Dept) Proven track record running SAP in a production environment; direct experience leading an S/4HANA or B-ONE implementation or migration is highly preferred Hands-on experience integrating SAP with multiple middleware systems in a heterogeneous landscape Prior experience in commodity trading, distribution, logistics, FMCG, or manufacturing in Indonesia Experience leading or sponsoring at least one substantive AI/ML or advanced analytics initiative end-to-end Demonstrated success managing IT budgets and large vendor portfolios Technical Knowledge SAP ecosystem: S/4HANA, B-ONE, SAP Integration Suite, Basis, ABAP literacy (not coding-level required) Integration patterns: REST/SOAP APIs, event-driven (Kafka), iPaaS (MuleSoft, Boomi, SAP IS, Azure Logic Apps) Cloud platforms (at least one of AWS / Azure / GCP) and hybrid architectures Data platforms and BI tooling Cybersecurity frameworks: ISO 27001; familiarity with UU PDP AI/ML at a literate level — enough to evaluate vendors, scope use cases, and challenge proposals (need not be a practitioner) Key Responsibilities: Strategic IT Leadership Define and execute a 3–5 year IT and digital transformation roadmap aligned with commercial strategy (trading volume growth, new commodity lines, geographic expansion, margin protection). SAP ERP Ownership Serve as the executive owner of the SAP environment (likely B-ONE). Middleware & Systems Integration Own the end-to-end integration architecture across SAP and the surrounding ecosystem — Procurement Management, Customs Management, Order Management, Compliance Management, and Warehouse Activity Management systems. Eliminate data silos and reconcile master data across systems (customers, vendors, materials, commodities, contracts). Digital Transformation & AI Lead the AI adoption agenda with a pragmatic, ROI-focused lens. Identify and prioritize use cases such as: Demand forecasting and inventory optimization for commodity stock Price/margin analytics and trade execution support Document automation for customs paperwork, B/L, invoices, COO, LC documents Compliance screening ( KYC/KYB) augmentation Warehouse activity optimization (slotting, dispatch scheduling, anomaly detection) Conversational interfaces for internal users to query ERP data Establish an AI governance framework covering data privacy, model risk, human-in-the-loop controls, and alignment with regulations. Data & Analytics Build a source of truth — typically a data warehouse or lakehouse — fed by SAP and all middleware. Establish data governance, master data management (MDM), and a BI layer (Power BI, Tableau, or similar) so trading, finance, and operations leaders make decisions on the same numbers. Cybersecurity & Compliance Own information security