金光纸业（中国）投资 聊一聊

Job Summary: The Data Product Manager is responsible for owning and driving delivery of data products and analytics/AI use cases that create measurable business value across company processes. This role translates business needs into a prioritized backlog, defines KPIs and single version of truth definitions, coordinates delivery with teams, and ensures UAT, adoption, and benefits realization. Key Responsibilities: Define and maintain a 12–18 month Data & AI roadmap spanning data foundation, analytics, and prioritized AI use cases. Build and manage a use-case portfolio with clear problem statements, KPI targets, ROI assumptions, and delivery milestones. Establish a benefits realization framework (baseline → target → actual), track post–go-live value, and report outcomes to leadership. Produce monthly performance reporting covering delivery status, adoption metrics, value delivered, key risks/issues, and next priorities. Coordinate cross-functional dependencies across business teams, IT, vendors, and regions (data access, extracts, integrations). Maintain delivery governance: manage RAID (risks, assumptions, issues, dependencies), escalate blockers, and ensure transparent progress tracking. Align stakeholders Ｏn timelines, trade-offs, and scope changes; manage scope through a structured change control process. Partner with the Data/AI Lead and governance owners to assign data owners and stewards across priority domains. Ensure every release meets core standards: KPI definitions, data dictionary updates, and data quality checks completed. Support data issue triage and prioritization, driving remediation of master data gaps, inconsistent definitions, and recurring quality issues. Qualifications and Experience: 8–12 years of experience in data, analytics, and/or AI roles, including 3–5 years leading delivery teams or major workstreams. Proven track record delivering enterprise data/analytics platforms and business-facing use cases, not Ｏnly technical components. Strong knowledge of data modelling, data integration patterns (batch, CDC, API), and enterprise system data across ERP/CRM/HR domains. Working knowledge of data security and data governance principles, including RBAC, data classification, PIPL, and basic privacy controls. Strong stakeholder management and communication skills, with the ability to align business and IT teams and drive decisions. Skills: Able to work independently and thrive in a fast-paced, evolving environment; proactive and outcomes-focused. Experience with cloud platforms preferably Microsoft Azure (AWS exposure is a plus), data visualisation, and AI tools, Hands-on experience with modern cloud data platforms and architectures, including lakehouse/warehouse patterns and scalable data pipelines. Strong business acumen, with experience in at least Ｏne domain such as Sales/Order-to-Cash, customer service operations, or HR reporting/people analytics. Exposure to manufacturing/OT data and systems (e.g., MES, historians/PI) is an advantage.