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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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Experience with "big data" and cloud computing technologies like BigQuery, Snowflake, and/or dbt. Enthusiasm for learning and sharing analytical methods to help grow a collaborative Data Science team and data-forward company culture.
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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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Experience with at least one major Massively Parallel Processing (MPP) or cloud database technology (Snowflake, Redshift, Big Query) Expanding, scaling, and standardizing the core foundational principles through consistent observability, lineage, data quality, logging, and alerting across all engineering teams in the Data organization is imperative to the creation of a single pane of glass.
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5+ years hands-on experience with the Big Data stack (HDFS, SPARK, MapReduce, Hadoop, Sqoop, Pig, Hive, Hbase, Flume, Kafka) A&I Data Service help to create data-driven organizations by providing the right solutions in Big Data technologies, Master Data Management, Business Intelligence Analytics by taking advantage of the Cloud based computing and storage.
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Undergraduate teaching experience in core topics in Data Science such as programming, data mining, data visualization, Parallel and Distributed Computing, Machine Learning, Big Data Engineering and, Probability and Statistics will be considered an asset.
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Developer experience in big data or warehouse (Hadoop, DB2 LUW) environment. AWS Data Engineer(Python) Securing data using IAM and Active Directory. AWS Data Engineer.
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Experience with Snowflake/BigQuery, Google Dataproc/Databricks or any big data frameworks on Spark. Enable functionality to support analysis, model optimization, statistical testing, model versioning, deployment and monitoring of model and data.
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Strong programming skills in Python and SQL. - Familiarity with big data processing frameworks such as Apache Spark. - Proficiency in Azure services such as Azure Data Lake Storage, Azure SQL Database, Azure Data Factory, Azure Synapse, and Azure Databricks.
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Familiarity with big data technologies such as Spark, Snowflake, Databricks, or EMR. You will be embedded on the Orchestration team that runs workflow scheduling applications and data ingestion infrastructure that helps power the analytics, operations, and data science behind our flagship streaming applications - Disney+, Hulu, ESPN+, and Star.
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By using SQL, Tableau, and Looker to create more sophisticated predictive modeling techniques and data visualizations to provide better revenue projections. If you’re doing Financial Planning and Analysis modeling inside a big media or ad tech company, come take your programmatic game to the top.
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Present or past Experience in analytic tools such as R, Python, AWS, and Databricks to build advanced analytic models, and exposure to accessing data from cloud platforms and big data systems such as Hadoop HDFS & Hive would be an advantage.
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We are looking for a passionate Software Engineer, Big-Data Engineer, Machine-Learning Engineer, Full-stack Engineer, or UI/UX Engineer, who can contribute and make a difference in any of the different components of our Knowledge Graph Platform.
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Experience with "big data" and cloud computing technologies like Redshift, Hadoop, Hive, BigQuery. We’re looking for an outstanding technical leader in economics and data science who specializes in statistical modeling, causal inference, and/or structural analysis to advance data-centric decision-making at Duolingo.
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Strong experience with machine learning technology, such as: big data stack, Python, R, and visualization techniques. Extensive experience with, both traditional SQL and modern NoSQL data stores including SQL, and large-scale distributed systems such as Hadoop and or working in Snowflake/Databricks.
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