【美国】数据仓库专家-rednote

主要职责 负责设计、构建并维护公司级基础数据平台与公共数据层，为社区、电商、广告等核心业务提供通用、稳定、高性能的数据能力支持，提升数据驱动业务的整体效率。 深入各业务领域，主导专题数据仓库与数据产品的建设，提供精准、易用的数据服务与分析模型，直接支持战略决策与业务运营。 建立并推行公司级数据治理体系，融合业务需求、元数据管理与技术实现，持续优化数据资源成本，全面提升数据质量、一致性、安全性与产出稳定性。 Key Responsibilities: Design, build, and maintain the company's foundational data platform and common data layers to deliver general, stable, and high-performance data capabilities for core business domains. Improve the overall efficiency of data-driven business operations. Dive deep into various business areas to lead the development of domain-specific data warehouses and data products. Deliver accurate, user-friendly data services and analytical models to directly support strategic decision-making and daily business operations. Establish and implement a company-wide data governance framework. Integrate business requirements, metadata management, and technical implementation to continuously optimize data resource costs while enhancing data quality, consistency, security, and pipeline stability.

任职要求 拥有计算机科学、信息技术或相关领域的学士及以上学位，具备3年以上相关领域工作经验。 拥有扎实的数据仓库研发经验，深刻理解从数据集成、建模到服务化的完整数据体系建设流程，并能持续推动其优化与价值实现。 掌握数据管理治理的核心理论与最佳实践，熟悉数据治理、数据标准、企业级数据建模、元数据管理及主数据管理等相关方法论。 精通大数据技术生态，具备扎实的实时或离线数据管道开发能力。熟练掌握Hive、Kafka、Spark、Flink、HBase等至少多项技术并拥有实际项目经验。 具备卓越的快速学习能力、出色的跨团队沟通与协作能力，以及强大的逻辑思维与复杂问题解决能力。 能够在英文工作环境中进行有效沟通（书面及口语），与全球团队顺畅协作。 Qualifications: Bachelor's degree or higher in Computer Science, Information Technology, or a related field, with up to 3 years of relevant work experience. Solid experience in data warehouse development, with a deep understanding of the end-to-end data architecture lifecycle—from data integration and modeling to serving—and a proven ability to continuously optimize and deliver business value. Strong knowledge of data management and governance principles and best practices, including familiarity with data governance, data standards, enterprise data modeling, metadata management, and master data management methodologies. Proficiency in big data technologies and ecosystems, with hands-on experience in building real-time or batch data pipelines. Practical project experience with multiple technologies such as Hive, Kafka, Spark, Flink, HBase, etc., is required. Excellent ability to learn quickly, strong cross-team communication and collaboration skills, and superior logical thinking and problem-solving capabilities. Ability to communicate effectively in English (both written and spoken) and collaborate seamlessly within a global team environment.