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Establish robust security measures for protecting sensitive Big Data (Hadoop / Trino/ Spark/ Kafka /Airflow). With over 10 years of experience in the field of big data, top US customers such as Mastercard, Tripadvisor, and Roku choose us to develop innovative products.
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Some Experience to Big Data Tools such as: Hadoop, HDFS, ADLS, ADF, Spark, Kafka, Databricks, Dremio etc. Some Experience to Big Data Tools such as: Hadoop, HDFS, ADLS, ADF, Spark, Kafka, Databricks, Dremio etc.
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3+ years of experience in designing, building, and deploying production-level data pipelines using tools from Hadoop stack (HDFS, Hive, Spark, Streaming, HBase, Kafka, Oozie, NiFi etc.) As a Sr Engr Cslt - Data Engineer within the Artificial Intelligence and Data Organization (AI&D), you will manage various activities including artificial intelligence, data engineering, operations automation, security remediation and industry leading Omni channel technology to improve the efficiency, customer experience and profitability of the company.
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Experience with large scale enterprise applications using big data open-source solutions such as Spark, Kafka, Elastic Search / Solr and Hadoop, HBase. Experience or knowledge of basic programming and DB's technologies (SQL, Python, Cassandra, PostgreSQL, AWS Aurora, AWS RDS , MongoDB, Redis, Couchbase, Oracle, MySQL, Teradata.
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3+ years experience with Distributed data/computing tools (MapReduce, Hadoop, Hive, EMR, Kafka, Spark, Gurobi, or MySQL) Utilize programming languages like Java, Scala, Python and Open Source RDBMS and NoSQL databases and Cloud based data warehousing services such as Redshift and Snowflake.
$4 - $10RemoteExpandApply NowActive JobUpdated 5 days ago - UpvoteDownvoteShare Job
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Experience with data engineering and analytics leveraging Hadoop, Accumulo, Kafka and dashboard development with Tableau. 10+ years of experience managing and leading efforts with DevSecOps tools, including Jenkins, Gitlab, ElasticSearch, Kibana, Prometheus, Grafana, or Logstash, infrastructure as code (IaC) and configuration management tools, such as Terraform or CloudFormation or Ansible, containerization tools and technologies using Docker Enterprise, Kubernetes, or OpenShift.
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Experience in traditional and modern Big Data technologies (HDFS, Hadoop, Hive, Pig, Sqoop, Kafka, Apache Spark, hBase, Oozie, No SQL databases) Experience in traditional and modern Big Data technologies (HDFS, Hadoop, Hive, Pig, Sqoop, Kafka, Apache Spark, hBase, Oozie, No SQL databases.
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2+ years of data warehousing experience (Redshift or Snowflake) 2+ years of experience with a public cloud (AWS, Microsoft Azure, Google Cloud) 5+ years of experience in application development including Python, SQL, Scala, or Java.
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Ability to investigate/research issues, determines impact, and provide solutionsStrong knowledge, implementation skills, and experience with security processes involving Java-Hadoop communication, Spark Streaming, and Kafka.
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5+ years of experience with Distributed data and computing tools, including Spark, Databricks, Hadoop, Nifi, Kafka, Scala, or Java. 5+ years of experience with Distributed data and computing tools, including Spark, Databricks, Hadoop, Nifi, Kafka, Scala, or Java.
$84,600 - $193,000 a yearExpandApply NowActive JobUpdated 5 days ago - UpvoteDownvoteShare Job
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Hands on in Hadoop Ecosystem (Kafka, Spark, Scala, Hive) is a plus. Site reliability engineering (SRE) fuses the software engineering and operations disciplines. Knowledge/Experience in Core Java, GoLang, Rust,Python.
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Extensive experience with Kafka, Spark, Redis, Flink, Trino/Presto, Hadoop in complex on-premise and hybrid data environments. Technical Leadership: Leverage your deep expertise in data technologies such as Kafka, Spark, Redis, Flink, Trino/Presto, and Hadoop to lead the architecture and development of our data systems, ensuring optimal performance, reliability, and scalability.
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4+ years experience with Distributed data/computing tools (MapReduce, Hadoop, Hive, EMR, Kafka, Spark, Gurobi, or MySQL) At least 1 year experience with cloud computing (AWS, Microsoft Azure, Google Cloud.
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Google Cloud Platform (Data Proc, BigQuery) Data storage and analysis toolsets, including modern distributed technologies such as SparkSQL, Hadoop, Presto, Hive, Kafka, Cassandra, Redshift or other equivalent solutions.
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Deep knowledge in Hadoop ecosystem, like HDFS, Hive, MapReduce, presto etc. Expert in multiple distributed technologies (e.g. Spark/Storm, Kafka, Key Value Stores, Caching, Solr , Druid, etc.
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