Data Architecture

Key Responsibilities

负责企业级 Data Platform 与 AI Data Foundation 架构设计及实施，支撑 Life Science 行业客户 AI Transformation 项目落地；

主导传统 Data Warehouse 向 Modern Lakehouse Architecture 的规划与建设，打造统一的数据基础设施；

负责 Enterprise Semantic Layer（企业语义层）的设计与建设，构建统一业务指标体系、语义模型及数据消费能力；

与客户业务团队、数据团队及 AI 团队协作，推动数据平台能力与 AI Use Cases 的结合与落地；

负责数据平台架构治理、数据建模、性能优化及平台演进规划，为企业级 AI 应用提供高质量数据支撑；

领导架构设计、技术选型及项目交付工作，并指导团队完成解决方案实施。

Basic Qualifications

5年以上 Data Platform、Big Data 或 Data Architecture 相关经验，具备企业级数据平台规划与建设经验；

具备完整 Lakehouse Architecture 项目经验（Must Have），熟悉现代数据平台架构设计理念；

熟悉 AWS（优先）或 Azure 云平台数据技术栈，具备云端数据平台建设经验；

具备 Enterprise Data Platform 建设经验，能够主导数据平台架构设计及技术治理；

具备扎实 SQL 能力，熟悉企业级数据模型设计、维度建模（Dimensional Modeling）及指标体系（KPI Framework）设计；

具备 Enterprise Semantic Layer 建设经验，能够设计业务语义模型、业务指标体系及统一数据消费层；

具备大型企业数据仓库现代化改造经验（Data Warehouse Modernization）者优先；

具备优秀的客户沟通及架构咨询能力，能够连接业务需求与技术方案。

Preferred Qualifications

Semantic Layer & Business Architecture

参与或主导过 Enterprise Semantic Layer 建设项目；

熟悉以下一种或多种技术/方法论：

CubeJS

dbt Semantic Layer

Databricks Metric View

Semantic Modeling

Business Metrics Framework

KPI Governance

具备从业务指标定义到语义模型设计的完整实践经验。

Lakehouse & Data Platform

深刻理解 Lakehouse Architecture 设计原则；

具有 Databricks、Snowflake、AWS Lake Formation、Delta Lake 等相关项目经验；

具备 Data Lake Direct Query（数据湖直算）及查询性能优化经验；

有大规模企业级平台建设和架构治理经验。

Advanced Data Engineering

具备 Streaming Data Processing 经验（Kafka、Spark Streaming、Flink 等）；

熟悉实时数据架构设计及数据处理优化；

具备 AI Data Platform 或 GenAI Data Foundation 项目经验者优先。

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