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5+ years of experience with Distributed data and computing tools, including Spark, Databricks, Hadoop, Hive, AWS EMR, or Kafka. As a lead big data engineer at Booz Allen, you’ll use your expertise to lead data engineering activities on some of the industry's most mission-driven projects.
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1+ years’ experience in Big Data Distributed ecosystems (Hadoop, SPARK, Unity Catalog & Delta Lake) 1+ years’ experience in Big Data Distributed systems such as Databricks, AWS EMR, AWS Glue etc.
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Experience in developing partner led sales in collaboration with data platform and tool vendorsIn-depth knowledge of big data technologies such as Hadoop, Spark, Kafka, and cloud platforms such as AWS, Azure, GCP, Snowflake, Databricks, etc.
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At least 4 years of experience in data engineering working with Big Data Technologies: Apache Spark, Pyspark, Hadoop, and DataBricks with delta lake. Experience with Apache Airflow, Hive, Snowflake, Kafka, Python.
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5+ years working experience with key open source big-data projects as a contributor or committer including Apache Spark, Apache Flink, Trino, Apache Kafka, Apache Hive, Apache Arrow, Apache Hadoop, Delta Lake, Apache Iceberg.
$419,750 a yearFull-timeExpandApply NowActive JobUpdated 6+ months ago - UpvoteDownvoteShare Job
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Strong experience with Hadoop, (HDFS), Spark, Kafka NoSQL, Cassandra, HBase, S3 protocol, ObjectStore and with processing large data stores. Architect and design big data storage and analytic solutions on Hadoop-based platform, create custom analytic and data mining algorithms to improve performance.
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Implement and utilize leading big data methodologies (AWS, Hadoop/EMR, Spark, Kafka, Snowflake and Talend) with cloud/on premise hybrid hosting solutions, on a multi-team/product level.
$184,920 a yearFull-timeExpandApply NowActive JobUpdated 3 days ago - UpvoteDownvoteShare Job
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In HADOOP , you'll be given an introduction to BIG DATA, APACHE HADOOP, HADOOP ECOSYSTEM, CLOUDERA QUICKSTART VM along with core concepts of the Hadoop framework including MapReduce, HIVE, PIG, SQOOP, FLUME, HBASE, OOZIE.
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Responsible for utilizing big data technologies (e.g., Apache Hive, Apache, Pig, Apache Spark, MapReduce, Hadoop, and MongoDB) and knowledge of data science models to analyze large amounts of data and create valuable insights for supporting the mission.
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Proven ability to handle and process large volumes of data and ability to utilize big data frameworks and tools such as Apache Spark, Hadoop or Kafka for real-time data ingestion and processing.
$230,000 a yearFull-timeExpandApply NowActive JobUpdated 14 days ago - UpvoteDownvoteShare Job
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Experience with big data tools and architectures, such as Cloudera Hadoop, HDFS, Hive, and Spark. YOUR SKILLS AND EXPERTISEBachelor’s degree in computer science, data science or a related field with five (5) or more years of working as a data engineer, ETL developer and/or data warehouse DBA.STANDOUT QUALIFICATIONS:Experience with Cloud-based data services and solutions (Azure Synapse / Data Lake, AWS RedShift, Snowflake, GCP Big Query)Experience partnering with Analytics and Data Science teams in building out production grade GenAI/ML solutions.
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Experience with big data technologies such as Apache Hadoop, Spark, Kafka, and others. Utilize Databricks for big data processing and streaming analytics. The ideal candidate will have a robust background in big data analytics, data engineering, and cloud computing, with a particular focus on building and optimizing data lakes on AWS. This role is crucial for designing, implementing, and managing advanced data solutions using AWS and Data Lakehouse platforms.
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THE ROLE:As a key member in the Advanced Data Analytics team, the Data Analyst will work with this and a cross-functional team to develop and execute the data analytics strategy and apply to Oshkosh Corporation products.
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Experience with cloud computing platforms (, AWS, Azure, GCP) and cloud native computingProficiency in programming languages like Python, Java, Scala, C#, SQLExpertise in big data technologies such as Hadoop, Spark, Kafka, and NoSQL databasesKnowledge of data modeling, ETL processes, and data warehousing conceptsExceptional problem-solving abilities and teamwork skills.
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Data Technologies: Kafka, Spark, Hadoop, Presto, Alloy – a data management and data governance platform. Kafka, Spark, Hadoop, MongoDB, ElasticSearch, MemSQL, Sybase IQ / ASE.
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hadoop kafka big data jobs Company: Capital One
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