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Open nowPosted 144 days ago

数据工程师（业务数仓方向）

acnc6zeentra/index41 open roles

Where
Shanghai, Chinese Mainland
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Your applicationOpen now数据工程师（业务数仓方向）acnc6zeentra/index · Shanghai, Chinese Mainland

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Share of postings closed within
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  4. 19.3%14 days
  5. 35.6%30 days
  6. 57.8%60 days
This job: posted 144 days ago

The posting

一、职位描述 本职位侧重于数据管道的构建与数据架构的设计。你不仅需要解决大规模业务数仓（尤其是海量用户行为数据体系）的建模与治理问题，还要负责为 AI 模型（预训练、微调）构建高质量、自动化的数据流转和特征处理体系。我们希望你具备极强的数据敏感度与业务 Sense，对数据的准确性、产出时效以及数据带来的业务价值负责。

二、岗位职责 1. 用户行为与业务数仓建设：主导核心业务数仓与用户行为分析（UBA）数据体系的架构设计，构建合理的长短周期归因、漏斗、路径等核心业务模型，支撑精细化运营及算法推荐。 2. 海量数据管道研发：设计并实现高容错、低延迟的数据管道（Pipeline），处理涵盖结构化业务日志、高并发用户行为埋点及多模态的大规模离线/实时数据。 3. AI 数据流转体系：研发针对 AI 场景的数据处理流水线，包括大规模语料清洗、去重、特征工程（Feature Engineering）及向量化处理。 4. 数据治理与成本调优：建立完善的数据质量监控与血缘追踪链路。统筹计算与存储成本，通过任务调优和资源治理，解决数据倾斜（Data Skew）、OOM 及高频查询瓶颈等生产级问题。

一、任职要求 1. 3 年以上数据开发或数仓架构经验，熟练掌握 SQL，精通 Python 或 Scala。 2. 丰富的用户行为分析经验：具备从 0 到 1 构建海量用户行为分析数仓的实战经验，深入理解流量埋点规范、事件模型（Event-Tracking）及常见的业务分析场景原理。 3. 深入理解 Hadoop/Spark/Flink 生态，具备大规模离线与实时数据处理的生产环境实战经验。 4. 具备优秀的业务理解与抽象能力，能迅速理清错综复杂的业务依赖，将非标的现实世界逻辑转化为清晰、高内聚的数据模型。 5. 熟悉现代数据工程工具链（如 CI/CD、Airflow、dbt），有严谨的代码规范、数据测试和质量管理意识。

二、加分项 1. 【核心加分】具备大规模复杂业务场景的实战与治理经验（如日均百亿级数据增量、高吞吐打点日志流、复杂的 DAG 调度依赖链）。 2. 【核心加分】具备 AI 数据工程经验，如大模型预训练语料处理、多模态数据集构建或向量数据库落地经验。

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