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Data Engineer- Sunrise, FL (Hybrid)-C2C-Only local at Remote, Remote, USA

Email: [email protected]

From: sudharsan.s, Vysystems [email protected] Reply to:   [email protected] Hands-on experience with GCP, google composer, bigQuery and bigTable 3 to 7 years of experience within Data Engineering/ Data Warehousing using Big Data Hands-on experience on writing and understanding complex SQL(Hive/PySpark-dataframes), optimizing joins while processing huge amount of data Hands-on experience with programming using Python/Scala Understanding of Cloud Native Principles and architectures and Experience in creating platform level cloud native system architecture with low latency, high throughput, and high availability. Have experience in designing and building Cloud native applications. Experience in cloud platforms like Docker, Kubernetes, OpenShift are a plus. Expert on Hadoop and Spark Architecture and its working principle Experience in UNIX shell scripting Experience with NoSQL i.e., HBase, Couchbase, MongoDB is good to have Teamwork & ability to multi-task Excellent communication skills Hands-on experience with GCP, google composer, bigQuery and bigTable 3 to 7 years of experience within Data Engineering/ Data Warehousing using Big Data Hands-on experience on writing and understanding complex SQL(Hive/PySpark-dataframes), optimizing joins while processing huge amount of data Hands-on experience with programming using Python/Scala Understanding of Cloud Native Principles and architectures and Experience in creating platform level cloud native system architecture with low latency, high throughput, and high availability. Have experience in designing and building Cloud native applications. Experience in cloud platforms like Docker, Kubernetes, OpenShift are a plus. Expert on Hadoop and Spark Architecture and its working principle Experience in UNIX shell scripting Experience with NoSQL i.e., HBase, Couchbase, MongoDB is good to have Teamwork & ability to multi-task Excellent communication skills Keywords:

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Wed Sep 06 03:47:00 UTC 2023

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