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Design and implement distributed data processing pipelines using Spark, Hive, Python, Airflow, and other tools and languages prevalent in the Hadoop ecosystem. Development skills around Hadoop, Spark, PySpark, Hive.
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You have an area of focus where you are a subject matter expert in technologies such as analytics, artificial intelligence, machine learning, security, some facet of big data ecosystem (e.g. Hadoop), or database expertise.
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Expertise and demonstrated experience in Hadoop ecosystem components: HIVE, HDFS, SPARK. Expertise and demonstrated experience in Hadoop ecosystem components: HIVE, HDFS, SPARK. UI/UX development experience s.
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Expert knowledge and experience in Databricks, Lake House, Structured Streaming, Kafka, Delta Lake, Delta Live table, Delta shareetc. Explore and build proof of concepts using open source NOSQL technologies such as HBase, DynamoDB, Cassandra and Distributed Stream Processing frameworks like Apache Spark, Kafka stream.
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3+ years of experience with distributed data/computing tools (MapReduce, Hadoop, Hive, EMR, Kafka, Spark, Gurobi, or MySQL) The Machine Learning Experience (MLX) team supports an internally hosted Model Training ecosystem running critical infrastructure for machine learning and data analysis across Capital One. You will get an opportunity to collaborate on the 1000's of models being trained on the platform by 4000+ users and dive deep into the unique engineering challenges we have around compute, data access, security and scale.
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Knowledge and/or experience working within the Teradata, Hadoop or other big data distributed ecosystem. Knowledge and/or experience working within the Teradata, Hadoop or other big data distributed ecosystem.
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Utilize programming languages like Java, Python, SQL, Node, Go, and Scala, Open Source RDBMS and NoSQL databases, Container Orchestration services including Docker and Kubernetes, and a variety of AWS tools and services.
$165,100 a yearExpandApply NowActive JobUpdated 5 days ago - UpvoteDownvoteShare Job
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We bring together a unique mix of Data Science capabilities and technology expertise across the Big Data ecosystem including Hadoop, NoSQL, NewSQL, MPP databases, machine learning, and innovative visualization.
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This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Center 2 (19050), United States of America, McLean, VirginiaSenior Software Engineer, Back End (Python, Kubernetes, AWS)Do you love building and pioneering in the technology space.
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1+ years of experience with AWS, GCP, Azure, or another cloud service. 5+ years of experience in at least one of the following: Java, Scala, Python, Go, or Node.js. 2+ years of experience with Kubernetes or Docker.
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At Uplight, we are motivating energy users and providers to accelerate the clean energy ecosystem. Familiarity with big data frameworks, Hadoop/MapReduce, HDFS, HBase or others. We are B Corp certified, enabling us to put our values into action by not only making decisions for the benefit of our shareholders, but also for our customers, environment, employees, and community.
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We use diverse technology stacks such as Snowflake, HANA, Hadoop, Spark, Cassandra, SingleStore, and beyond. We are looking for a Technical Product Manager to develop a deep understanding of various products and build a clear vision of how the product will evolve in Apple's Ecosystem.
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Proficiency in Hadoop ecosystem components such as HDFS, YARN, MapReduce, Hive, Spark, and HBase. As a Hadoop Platform Engineer, you will be responsible for designing, implementing, and managing our company's Hadoop infrastructure and data ecosystem.
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At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors, who love to solve real problems and meet real customer needs. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC.
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Design and implement distributed data processing pipelines using Spark, Hive, Python, and other tools and languages prevalent in the Hadoop ecosystem. As a Sr. Big Data Engineer, you will work with a variety of talented teammates and be a driving force in technical initiatives that will accelerate analytics.
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