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pooytr1
V2EX  ›  酷工作

微软北京 Azure Big Data team 开放海量 HC, 等你来!

  •  
  •   pooytr1 · 2020-11-18 19:41:47 +08:00 · 2084 次点击
    这是一个创建于 1451 天前的主题,其中的信息可能已经有所发展或是发生改变。

    微软北京大量 HC! 可直接内推到本组,岗位列表及 JD 可查看:

    https://careers.microsoft.com/us/en/search-results?qcity=Beijing&qstate=Beijing&qcountry=China&keywords=azure%20big%20data&subCategory=Software%20Engineering

    感兴趣的发送简历或联系 pengxu(AT)microsoft(DOT)com. 我会帮助内推😄

    开放岗位包括:

    • PM
    • 全栈
    • 前端
    • 机器学习
    • streaming

    Azure Big Data Team:

    Azure Big Data team (Azure Synapse Analytics, Azure HDInsight, Azure Stream Analytics, Azure Datalake Analytics, Azure Databricks and Cosmos) present exciting challenges in technologies such as big-data, cloud, distributed computing, artificial intelligence, storage and open-source. We build reliable, highly scalable and highly performing distributed systems for data analytics on Azure. Azure HDInsight is one of the fastest growing Azure services that offers popular open source technologies, such as Spark, Hadoop, Kafka, HBase and many others in a form that is easy for customers to use. We work with various open-source technologies including Spark, Hadoop, Yarn, etc. and make contributions to these technologies. We are running one of the world’s largest big data cluster which has more than 25,000 machine, stored more than 10,000PB data and run tens of thousands of jobs everyday across search, ads, Office, Xbox, etc. Azure Stream Analytics is an event-processing engine that allows users to examine high volumes streaming data at scale. We are supporting massively parallel complex streaming processing in Azure.

    4 条回复    2020-12-08 17:12:40 +08:00
    mars0prince
        1
    mars0prince  
       2020-11-18 20:04:22 +08:00
    英语有要求吗
    pooytr1
        2
    pooytr1  
    OP
       2020-11-18 22:02:39 +08:00
    @mars0prince 能做到工作中的基本表达就可以,没有特别高的要求。
    HanMeiM
        3
    HanMeiM  
       2020-11-19 10:22:01 +08:00
    这个全栈跟我想象中的全栈好像不太一样啊。
    grsky360
        4
    grsky360  
       2020-12-08 17:12:40 +08:00
    @pooytr1 之前在 streaming 那边挂了, 还能在这边投么
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