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Advanced knowledge of cloud computing technologies such as: Apache Spark, Azure Data Factory, Azure DevOps, Azure ML (Machine Learning), Hadoop, Microsoft Azure, Databricks, AWS, Google Cloud.
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Technologies & Skills: Java, Apache Spark, Delta Lake, Spark SQL, MySQL, Kafka, drools, Spring Boot, REST APIs, Maven, Jenkins, Docker, Kubernetes. 3-5+ years working on Big Data projects focused on real time processing and Big Data pipeline optimization (Delta lake, Apache Spark.
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We also work with or are looking at working with technologies such as SQL, Kafka, Kafka Streams, Flink, Spark, AWS (AWS Analytics Services, Columnar storage, Athena), Google Cloud (GKE, App Engine, Pub/Sub), Riak and Go.
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Experience with distributed data or computing tools including Spark, Databricks, Hadoop, Hive, AWS EMR, or Kafka. Experience with a public cloud, including AWS, Microsoft Azure, or Google Cloud.
$75,600 - $172,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Big plus memory model data structures concurrency and Multithreading strong testing flint Apache Spark kafka streams etc. Experience with high speed distributed computing frameworks like FLINK, Apache Spark, Kafka Streams, etc.
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4+ years Experience with technologies Apache Mesos, Marathon, or Apache Spark. At least 3 years of experience in Cloud Native technologies (Amazon Web Services, Microsoft Azure, Google Cloud Platform.
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Working with both structured and unstructured data, recognize patterns within data and generate insights/deliver value; streaming analytics using tools Spark, Kafka, Storm and cloud services AWS, Azure Cloud, Google Cloud.
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Big Data & Streaming: 2+ years using big data and/or streaming technologies (e.g. Apache Spark, Apache Kafka, Apache Flink) Design, develop and deliver scalable, robust and highly re-usable components using technologies such as Python, Java, AWS serverless (Lambda, Glue), Apache Spark, Apache Kafka and REST.
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Familiarity with big data technologies, (e.g., Elastic Search, Apache Hadoop, Spark, Kafka, etc. Experience with Apache Spark, Apache Streaming, and Jupyter Hub+ Event Reporter to introduce ML and pattern recognition to discover hidden insights.
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Experience with streaming platforms and data engineering such as Apache Kafka or Apache Spark a plus. Experience with cloud providers like Azure, AWS, and/or GCP and familiarity with serverless technologies such as AWS Lambda, Azure Functions, or Google Cloud Functions.
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Solutions include API-driven clients, microservice architectures, event-driven integrations, cloud deployments, serverless applications, and web and portal front ends. Fringe –A company paid stipend program for personalized lifestyle benefits, allowing employees to choose benefits that matter most to them – ranging from vendors like Netflix, Spotify, and GrubHub to services like student loan repayment, travel, fitness, and more.
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The Senior Data Platform Developer, Infrastructure supports the existing big data infrastructure on Google Cloud Platform, Google BigQuery ensuring data is continuously and promptly available for analysis by the data science team.
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Knowledge of big data technologies such as Apache Spark, Hadoop, or Kafka. Knowledge of big data technologies such as Apache Spark, Hadoop, or Kafka. Design and implement scalable data pipelines using AWS services such as Glue, Redshift, S3, Lambda, EMR, Athena.
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Big Data implementation – using Open Source and NoSQL technologies such as Databricks, Spark, Spark Streaming, Kafka, Storm, Zeppelin, Scala, Software development, Hadoop Hive, Hadoop Map Reduce, Hadoop Clusters, Cosmos DB, Azure Data Lake Storage (ADLS.
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Experience with big data technologies such as Apache Beam, Apache Spark, Hadoop, Apache Flink and AWS Glue. Experience with cloud platforms such as Google Cloud Platform (GCP), Amazon Web Services (AWS), or Microsoft Azure.
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hadoop kafka google cloud apache spark jobs Company: Brainwave Professionals
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