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Hands-on experience with AWS services such as S3, Glue, Redshift, EMR, Athena, etc. Experience with big data technologies such as Apache Hadoop, Spark, Kafka, and others. In this role, the successful candidate will drive our efforts to support cloud initiatives for the National Oceanic and Atmospheric Administration (NOAA) and National Environmental Satellite, Data, and Information Service (NESDIS) with a focus on architecting and provisioning enterprise-level Cloud services, including Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS.
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5+ years hands-on experience with the Big Data stack (HDFS, SPARK, MapReduce, Hadoop, Sqoop, Pig, Hive, Hbase, Flume, Kafka) 5+ years hands-on experience with related/complementary open source software platforms and languages (e.g. Java, Linux, Apache, Perl/Python/PHP, Chef, Scala.
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Hands-on experience with ETL (Extract-Transform-Load) tools (e.g. Informatica, Talend, Pentaho) Create information solutions covering data security, data privacy, metadata management, multi-tenancy and mixed workload management across Hadoop and NoSQL platforms, spanning on-premise and Cloud based deployments.
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Experience helping customers build distributed systems or streaming solutions that use Apache Kafka alongside technologies such as Spark, Flink, Hadoop, Cassandra, etc. Hands on knowledge of one or more key cloud vendors (AWS, GCP and Azure.
$180,855 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Hands-on programming experience in Apache Spark using SparkSQL and Spark Streaming or Apache Storm. Hands-on expertise in cloud services like AWS, and/or Microsoft Azure. Hands on experience with major components like Hive, Spark, and MapReduce.
$227,900 a yearFull-timeExpandApply NowActive JobUpdated 3 days ago - UpvoteDownvoteShare Job
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Design and develop data ingestion programs to process large data sets in Batch mode using Hadoop, Spark, Azure Synapse, and Databricks. Develop data ingestion programs to ingest real-time data from LIVE sources using Apache Kafka, Spark Streaming and related technologies.
$227,900 a yearFull-timeExpandApply NowActive JobUpdated 5 days ago - UpvoteDownvoteShare Job
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Solid understanding of ETL methodologies in a multi-tiered stack, integrating with Big Data systems like Hadoop and Cassandra. Knowledge of Spark and Kafka integration with multiple Spark jobs to consume messages from multiple Kafka partitions.
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Extensive hands-on experience in Contract First/Design First Software Development for Microservices and Data Products, and CI/CD using the Service & Data ContractsBroad knowledge across data engineering (e.g., ETL/ELT, data modeling), data governance (e.g., data modeling, data classification, data catalog and lineage), batch and real-time streaming data platforms (e.g., Airflow, Spark, Hadoop, Hive, Kafka, dbt), and cloud services (e.g., GCS, BigQuery, Vertex AI, Databricks.
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Experience in the development of Hadoop APIs and MapReduce jobs for large scale data processing. Good knowledge in apache Kafka & Apache Flume. Strong understanding & familiarity with all Hadoop Ecosystem components and Hadoop Administrative Fundamentals.
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Extensive hands-on experience implementing Lakehouse architecture using Databricks Data Engineering platform, SQL Analytics, Delta Lake, and Unity Catalog. Familiarity with the Technology stack available in the industry for data management, data ingestion, capture, processing, and curation: Kafka, StreamSets, Qlik/Attunity, GoldenGate, Hadoop, Hive, Hbase, Cassandra, Spark, Flume, Hive, Impala, etc.
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Define and develop client specific best practices around data management within a Hadoop environment or cloud environment. Strong understanding of underlying Hadoop Architectural concepts and distributed computing paradigms.
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Experience in Data security (on the move, at rest) Experienced in Hadoop clustering and Auto scaling. And we’re counting on your unique voice and perspective to help EY become even better.
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Extensive hands-on experience implementing serverless real-time/near real-time architecture using Cloud native services (i.e., Azure, AWS or GCP Tech Stack), and Spark technologies (e.g., Spark Streaming, Spark ML.
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Minimum of 4 year’s of experience in Databricks engineering solutions on one of the Cloud platforms (Azure, AWS or GCP) Minimum of 4 year’s of experience in Data Architecture and delivery experience on one of the Cloud platforms (Azure, AWS or GCP.
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Minimum of 7 year’s of experience years of experience in Big Data/Hadoop, database and data warehouse architecture and delivery. You will be part of a highly collaborative and growing network of technology and data experts, who are taking on today’s biggest, most complex business challenges using the latest data and analytics technologies.
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hadoop kafka hands on jobs Title: architect
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