Job Description Job Overview Position. Java & Big Data Developer (Application migration from Hadoop to AWS) Location. Noida/Chennai Shifts. Night (US Shifts), 5 days' work from the office Please apply only if you are comfortable with total night shifts and 5 days of work from the office....
Job Description We are looking for a Big Data Engineer that will work on the collecting, storing, processing, and analyzing of huge sets of data. The primary focus will be on choosing optimal solutions to use for these purposes, then maintaining, implementing, and monitoring them. You will al...
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Senior Big Data Developer - K· 薪 PayPal 互联网 已上市 更换职位 职位关闭 资深Java开发工程师(算法工程) - K 携程集团 互联网 已上市 职位详情 上海 不限 本科 SQL 搜索引擎技术 分布式技术 Linux NoSQL Java Hadoop Spark Job Description Summary For more than 20 years, PayPal has remained at the...
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s job. They then proceed to create and build a dependable and adaptable big data infrastructure. They are in charge of data collection, storage, processing, and analysis systems. A Big Data Engineer is regarded as the data supply’s king. They make critical data easily accessible and usable ...
Job Description : Client is looking for a big data developer who can help in data ingestion with Python, Nifi, Scala, Spark, Kafka back ground 3+ years of hands-on experience with Big Data technologies – Specifically, Hadoop, Hive, Spark, Scala, Java, Sqoop and Pig Skilled in developm...
Senior Big Data Developer - K· 薪 PayPal 互联网 已上市 更换职位 招聘中 java研发工程师(海外用户增长方向) - K· 薪 拼多多集团-PDD 互联网 已上市 立即沟通 职位详情 SQL 搜索引擎技术 分布式技术 Linux NoSQL Java Hadoop Spark Job Description Summary For more than 20 years, PayPal has remained ...
Big Data projectsare often starting off like the first generation ofDW, reporting,OLAP, and dashboard projects (i.e., “if we built it they will come”). Whenever a new technology wave is hyped so extensively, there is a tendency for enterprises to buy into that hype and assume that th...
The job of a big data developer includes data transformation and data storage tasks. They are the ones who create and maintain data pipelines to put the data to good use. They may even work with data engineers to define and implement the process of data cleansing, transformation, and storage...