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Specific Application Support Knowledge for Messaging Service Expertise: Kafka, JMS, and MQ. As a Senior Azure Kafka Developer, you will be required to provide advanced technical support, addressing complex issues escalated from L1 support or directly from end-users.
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Experience in Apache Hive, Apache Spark, Apache Kafka. Experience in Apache Hive, Apache Spark, Apache Kafka. Continuous Integration tools such as Bamboo, Jenkins, or TFS. Atlassian products – BitBucket, JIRA, Confluence etc.
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Skills: Java, Microservices, Spring boot, Multithreading, Kafka, React. Skills: Java, Microservices, Spring boot, Multithreading, Kafka, React. Proficiency in working with relational databases (MySQL, PostgreSQL, etc.
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Experience with mainstream big data tools (e.g., MapReduce, Spark, Flink, Kafka, etc. Proficiency in mainstream ML libraries (e.g., TensorFlow, PyTorch, Spark ML, etc. A tech lead role to lead and deliver production-grade machine learning products from end to end to make Samsung Ads a key player in the mobile performance ads market.
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Come build the future of data streaming with the Amazon Managed Streaming for Kafka (MSK) team! Come build the future of data streaming with the Amazon Managed Streaming for Kafka (MSK) team! We are seeking builders for our Amazon MSK service, a fully managed service that makes it easy for customers to build and run applications that use Apach Development Engineer, Software, Development, Engineer, Customer Experience, AWS, Technology.
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Experience with designing and implementing log observability, metrics collections, metrics streaming services to ingest billions of events using Kinesis, Kafka, etc. Experience with designing and implementing log observability, metrics collections, metrics streaming services to ingest billions of events using Kinesis, Kafka, etc.
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Keywords: Java, Core Java, Data Structures, Angular, React, JavaScript, MongoDB, NoSQL, RabbitMQ, Message-Based Architecture, Messaging Tools, Communications Protocols, Kafka, Service Bus, Azure, AWS, Amazon Cloud Services, GCP, Google Cloud Platform, Commercial Software Development, Enterprise Software Development, Product Development Lifecycle (PDLC), Software Development Lifecycle (SDLC), Agile, Version Control Systems, SaaS, Scalable Systems, High Availability, Performance Optimization.
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Must have 2 years of experience working with AWS, Kafka, and Kubernetes. Enterprise services supporting an omni-channel retail business, particularly in the areas of payments and inventory. Must have 2 years of experience working with AWS, Kafka, and Kubernetes.
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Experience with some of the following technologies: Postgres or MySQL, Distributed high concurrency key-value storage (Redis, DynamoDB), Docker, AWS, Kubernetes, Kafka, Embedded systems (Raspbian, Embedded Linux, FreeRTOS.
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Python, Azure, Kafka, or Saltstack. DLVR is opening a remote engineering position to complement its existing staff located in Seattle and Phoenix and here is your opportunity to join a well funded, established startup as a Senior Software Engineer.
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Experience with big data processing frameworks, such as Apache Spark, Hadoop, or Apache Kafka on Azure. Experience with big data processing frameworks, such as Apache Spark, Hadoop, or Apache Kafka on Azure.
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Experience with distributed data and computing tools, including MapReduce, Hadoop, Hive, EMR, Kafka, Spark, Gurobi, or MySQL. As a data scientist, you're excited at the prospect of unlocking the secrets held by a data set, and you're fascinated by the possibilities presented by IoT, machine learning, and artificial intelligence.
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Knowledge of distributed data and computing tools, including MapReduce, Hadoop, Hive, EMR, Kafka, Spark, Gurobi, or MySQL. Experience designing, developing, and deploying interactive and user-friendly dashboards and applications, using Tableau, Power BI or Qlik Sense.
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Experience with the Hadoop eco system, including HDFS, YARN, Hive, Pig, and batch-oriented and streaming distributed processing methods such as Spark, Kafka, or Storm. Experience with the Hadoop eco system, including HDFS, YARN, Hive, Pig, and batch-oriented and streaming distributed processing methods such as Spark, Kafka, or Storm.
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Hands-on experience with Hadoop, Hive, Pig, Map Reduce, Spark, Rabbit MQ, Kafka, Flume. Hands-on experience with Hadoop, Hive, Pig, Map Reduce, Spark, Rabbit MQ, Kafka, Flume. Demonstrated experience with Ansible playbooks or puppet modules for virtual and physical instance provisioning, configuration management, patching, and software development.
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