岗位职责/Job Responsibilities：

Responsible for principles, guideline, process and measurable metrics definition and activities running in terms of data warehouse management, data lifecycle management, meta data management, data security, data quality and data development.

Play as a key enabler to balance compliance needs with value creation from the organizations' data assets.

Technical professionals and their business counterparts should deploy automated and scalable solutions for governance policy creation and enforcement in big data architectures.

Exercise authority and control over the management of data assets.

岗位要求/Job Requirements：

• Strong product management experience in enterprise data, analytics, AI, platform products, or digital transformation.

• Good understanding of data platforms, data engineering, analytics, data governance, metadata, MDM, data lake/warehouse, or BI ecosystems.

• Familiarity with Generative & Agentic AI, context & harness engineering, text-to-SQL, MLOps, DataOps, Data Engineering, Skills / MCP, or AI-enabled workflow automation.

• Ability to convert complex technical capabilities into business value, product requirements, and executive-ready communication.

• Strong stakeholder management across business, engineering, IT, architecture, and governance teams.

• Experience defining product KPIs, adoption metrics, ROI assumptions, and value realization plans.

• Customer-success mindset with strong communication, analytical thinking, and problem-solving skills.

• Comfortable working in ambiguity and shaping new product capabilities from concept to adoption.

• Active user of AI tools such as Codex, ChatGPT, Claude, Gemini, Microsoft Copilot, GitHub Copilot, Cursor, Devin, CrewAI, LangChain/LangGraph, AutoGen, or similar tools.

Experience Requirements

• 6+ years of experience in product management, data platform, analytics, AI, enterprise software, or digital transformation.

• 3+ years leading or managing enterprise data, AI, analytics, or platform product initiatives.

• Proven experience working with engineering and cross-functional teams to deliver enterprise technology products.

• Experience building roadmaps, business cases, user stories, adoption plans, and measurable product outcomes.

• Experience in a global enterprise environment is preferred.

• Databricks expert is strongly preferred.