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Extract Transform Load (ETL) experience using Spark, Kafka,Hadoop, or similar technologies. SummaryWe are looking for a Machine Learning Engineer, who has hands-onexperience in machine learning system development, Cloud computing, backenddevelopment and AI/ML. Candidate must have strong NLP exp.
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Js development experienceAt least 2+ years of Node.js dev experience, and async event/message-driven systems like ElasticSearch, Kafka/RMQ, etc. At least 2+ years of experience with relational (MySQL, postgres)/non-relational database systems (Cassandra, MongoDB, cockroach DB etc.,)At least 3+ years of experience with working in Linux based environmentRequired Skills: Node. JS, React.
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Experienced in Nginx, Kafka, MySQL, Cassandra, Redis, and big data platforms. Experienced in MySQL, Redis, Elastic Search, Kafka, and Cassandra. Experienced in Nginx, Kafka, MySQL, Cassandra, Redis, and big data platforms.
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Understating and experience of testing Distributed Computing systems, preferably Hadoop, Cassandra, Kafka is a strong plus. Java, Python, Distributed systems, API test automation, API Automation, Rest API Test automation, Kubernetes, AWS, Linux, Docker.
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Proven experience in data streaming systems and event ingestion services such as Azure Event Hubs or Apache Kafka. Proven experience in data streaming systems and event ingestion services such as Azure Event Hubs or Apache Kafka.
$120,000 - $250,000 a yearFull-timeExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
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Familiarity with MongoDB, Kafka/Firehose, Redis, Spark/Spark Streaming/Spark SQL, Redshift, or similar data warehousing solutions, amplifying data processing capabilities. Familiarity with MongoDB, Kafka/Firehose, Redis, Spark/Spark Streaming/Spark SQL, Redshift, or similar data warehousing solutions, amplifying data processing capabilities.
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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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LinkedIn has pioneered many well-known open-source infrastructure projects including Apache Kafka, Pinot, Azkaban, Samza, Venice, Datahub, Feather, etc. Being accompanied by a service dog. Java, Go, Rust, Python, Scala.
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Hadoop, Spark, Kafka, ETL Pipelines ) Experience with cloud computing platforms (AWS, Azure, Google Cloud, SnowFlake etc ) and big data technologies (eg. This data lake will serve as a foundational resource for AI-driven threat intelligence, connecting several SaaS services and managed solutions.
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Deep understanding of cloud platforms (AWS, Google Cloud, Azure) and big data technologies (Apache Spark, Kafka). Deep understanding of cloud platforms (AWS, Google Cloud, Azure) and big data technologies (Apache Spark, Kafka.
$130,000 - $200,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Deep technical expertise in GoLang, Python, GraphQL, Temporal, Helm, Prometheus, Kafka, PostgreSQL. Deep technical expertise in GoLang, Python, GraphQL, Temporal, Helm, Prometheus, Kafka, PostgreSQL.
$268,000 - $414,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Experience with stream-processing technologies like Apache Kafka and Apache Flink. The ideal candidate has a proven track record of building large scale enterprise products, and is a creative thinker, problem solver, learner, and a fantastic manager of people, and is motivated with engineering excellence.
$178,000 - $210,000 a yearFull-timeExpandApply NowActive JobUpdated 5 days ago - UpvoteDownvoteShare Job
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In order to accomplish this, we use state-of-the-art languages like Scala and Go, data technologies like Kafka and Aerospike, and agile development practices. Knowledge in one or more of the following: NoSQL (especially, but not only Cassandra), Queueing system experience (Kafka, RabbitMQ, ActiveMQ, MSMQ), Play framework, Akka library.
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Familiarity with CI/CD, ETL, big data tools, and mainstream ML libraries (e.g., MapReduce, Spark, Flink, Kafka, Docker, Kubernetes, TensorFlow, PyTorch, Spark ML, etc. Familiarity with CI/CD, ETL, big data tools, and mainstream ML libraries (e.g., MapReduce, Spark, Flink, Kafka, Docker, Kubernetes, TensorFlow, PyTorch, Spark ML, etc.
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Experience with Docker and Kubernetes, Apache Kafka, and Google Pub/Sub. Experience with microservices, preferably Spring Boot. Strong knowledge of relational databases, MySQL. Experience with Cloud Technologies.
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kafka job in Sunnyvale, CA
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