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Experience building big data pipelines with Hadoop, Java, Scala, and Spark. The ASE Search team powers search for iTunes, App Store, Apple Music, Apple TV, Podcasts, Books and more on iOS, macOS, tvOS, watchOS, web browsers, 3rd party devices, and Windows.
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These are the people who power Search for the App Store, Apple TV, Apple Music, Apple Podcasts, and Apple Books. -Support search on all devices (macOS, iOS, tvOS, watchOS, visionOS, Siri/HomePod, and more) globally in languages from Arabic to Russian and everything in between.
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Any level of experience with Lead design and development of the Big Data Analytics Platform by gathering requirements from the various stakeholders and converting it to technical design and implementation using various Big Data technologies like Apache Spark, Mapreduce, Mongodb etc and programming languages like Java, Scala, Python and build and maintain search related product using technologies including Lucene and Elasticsearch.
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Software development practices and management, leading diverse development teams using diverse technologiesSystem architecture, virtualization and cloud computing technologiesEncryption, PKI, RSA, Active Directory and NIST computer security guidelines and best practicesJava programming, Java Enterprise Edition and open source Java libraries and frameworks including servlet/web application and portlet JSRs, Spring and Hibernate.
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Expertise in building Big Data Services using open source technologies like Elastic Search, Flink, Logstash, Kakfa, MongoDB, Hadoop, Spark, Trino/Presto, Hive, Airflow, Splunk. Strong experience writing services/software in a Linux/UNIX environment in one or more of the following languages: Java, Python, Perl, Ruby, Go, Scala.
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Big Table , Elastic Search, PostgreSQL, GCS , Kafka with Schema Registry, AVRO Model ReactJS, REST API , Apache Camel , Java 11, Spring Boot WNCP (Kubernetes and Docker) Big Table , Elastic Search, PostgreSQL, GCS , Kafka with Schema Registry, AVRO Model ReactJS, REST API , Apache Camel , Java 11, Spring Boot WNCP (Kubernetes and Docker.
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Experience working with big data systems (Spark, EMR, Kafka, S3, Airflow) and programming languages (Java, Scala, or Python). Good understanding of system architecture, including experience with big data technologies, streaming architecture, and data pipelines.
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EXPERTISE TECHNOLOGYCloud, DevOps, RPA, SAP, Data warehouse, Business Intelligence, SFDC, Java, React js, Net, Embedded Technologies, Big Data and Hadoop, Abinitio, CyberArk, Dell Boomi, Golang, Mulesoft, Guideware, MarkLogic.
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Work on Search algorithm, web services, search indexing, data mining, big data, Hadoop, deep learning, recommendations, and performance by developing a Search platform at Adobe that would power Adobe Clouds such as Creative Cloud, Document Cloud and Marketing Cloud.
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Working knowledge in one of the following areas: machine learning, deep learning, backend, large-scale systems, data science, full-stack Experience with Big Data Frameworks, such as hadoop, spark, flink, etc.
$145,000 - $250,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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This person will working on all new green development projects utilizing an array of tools such as: JVM programming languages(Java/Springboot, Groovy, Python), Docker + Kubernetes, Javascript/React, Kafka, Elastic Search, Lucene, Spark, and Cassandra, DynamoDB as well as Neo4J. Obviously very few folks have touched/been hands-on with all of these tools in production.
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Powered byinnovative technology and operations, we have set out to transform the customer experience journey-from revolutionizing last-mile delivery to rethinking how customers search and discover on a truly mobileplatform.
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Thus, the ideal applicant will be a well-rounded full-stack developer whose experienced with or looking to dive into big data and cloud technologies. · Experience with JVM languages: Java(preferred), Scala, Groovy, and/or Python.
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NoSQL DB Experience preferred and background with Neo4J is a big plus. · Experience with Java and Springboot. Experience with Microservices and containerization tools(Docker, Kubernetes.
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Conceptual understanding of one or more of the following disciplines preferred big data technologies and distributions, metadata management products, commercial ETL tools, Bi and reporting tools, messaging systems, data warehousing, Java (language and run time environment), major version control systems, continuous integration/delivery tools, infrastructure automation and virtualization tools, major cloud, or rest API design and development.
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