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Processing Tools: Elasticsearch, YARN, Spark, Nifi and/or Docker. Much of our work contributes to innovative research in the fields of sensor science, signal processing, data fusion, artificial intelligence (AI), machine learning (ML), and augmented reality (AR.
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7+ years of experience in software engineering and machine learning, with a focus on building and maintaining ML infrastructure or Batch Compute infrastructure like YARN/Kubernetes/Mesos. Bonus point for experience working with cloud data processing technologies (Apache Spark, Ray, Dask, Flink, etc.
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Spark, Kafka, Elasticsearch, Kibana, Tomcat, stream processing, RDBMS, NoSQL databases, and so on. Deep understanding of technology including (but not limited to) Hadoop (Flume, HDFS, Hive, HBase, YARN etc.
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Experience with UI/UX development & design systems: CSS, Web Components, Less, Sass Experience or exposure in big data and event streaming technologies: Spark, Kafka, etc. NET, Python And Minimum of 3 years experience with databases and data modeling / design (SQL and NoSQL) And Minimum of 2 years in full stack development for cloud solutions (Azure or AWS) - Azure preferred Skills and Knowledge Experience or exposure in JavaScript development frameworks and tooling: Angular, React, VueJS, & Gulp, Grunt, Yarn, etc.
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Familiar with open source distributed scheduling/orchestration/storage frameworks, such as Kubernetes (K8S), Yarn (Flink, MapReduce), Mesos, Celery, HDFS, Redis, S3, etc., with rich practical experience in machine learning system development.
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Big Data Components/Frameworks such as Hadoop (MapR), Spark, Yarn, Kafka, Flink, ELK, etc. Big Data Components/Frameworks such as Hadoop (MapR), Spark, Yarn, Kafka, Flink, ELK, etc. 20 weeks paid parental leave for all parents, regardless of gender, offered for pregnancy, adoption or surrogacy.
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Extensive knowledge on Hadoop eco-system such as HDFS, Yarn, HIVE and SPARK. Excellent Shell, Python programming skills for automation requirement for repetitive dev-ops tasks Understanding of security tools like Kerberos and Ranger.
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This individual’s day-to-day work will involve using Java, Python, SQL, Big Data, Linux, git, and gradle to design and build software solutions that are fast, scalable, and flexible. Big Data querying tools such as Drill, Presto, Hive, Ojai, etc.
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Hadoop (or similar) Ecosystem (MapReduce, Yarn, HDFS, Hive, Spark, Presto, Pig, HBase) Hadoop (or similar) Ecosystem (MapReduce, Yarn, HDFS, Hive, Spark, Presto, Pig, HBase) Experience with traditional relational databases, NoSQL databases and/or distributed systems such as Hadoop/Hive, BigQuery, Redshift.
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With industry-leading fraud prevention and digital identity offerings, we help our clients grow revenue and protect against loss. 2 years of software development experience as a Python developer-Preferred.
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2+ years with Big Data Hadoop cluster (HDFS, Yarn, Hive, MapReduce frameworks), Spark, AWS EMR. Familiarity with Hadoop / Spark information architecture, Data Modeling, Machine Learning (ML.
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Initiate and monitor processes for consolidating, moving, and validating data between customer systems using Linux, spark, yarn, and other processes. Demonstrated experience utilizing big data technologies such as SPARK, IMPALA, and PYSPARK.
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Hands-on exp w/ Programming using Python & PySpark; Hadoop; HDFS, map-reduce, YARN, AWS EMR; Hive, HBase, parquet, ORC, Spark SQL, Sqoop, Apache Hudi; orchestrating ETL pipelines involving data sourcing, transformations & publishing using Apache Airflow; performance tuning apps in distributed computing enviros designing & developing data pipeline apps w/ Apache Kafka.
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Big Data: Apache Spark, YARN, Livy, ZooKeeper, Ranger, Knox, Polybase. Big Data: Apache Spark, YARN, Livy, ZooKeeper, Ranger, Knox, Polybase. Data Sources: MongoDB, Cloudera, Teradata, Oracle, DB2.
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Big Data such as Hadoop (MapR), Spark, Yarn. 6+ years of software development experience as a Spark/Scala developer. Big Data such as Hadoop (MapR), Spark, Yarn. Job Title: Big Data Engineer (4 position.
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