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Proficiency in one or more ETL Ab Initio tool sets Co>Operating Systems, GDE, EME, Express>It and Conduct>It or Apache Spark. Advanced in one or more programming language(s) and frameworks like Spring, JSON Rest Services, Kafka, MQ Proficiency in GIT, IntelliJ, Maven, Postman, Sql Developer, automation and continuous delivery methods Advanced knowledge of software applications and technical processes with considerable in-depth knowledge in one or more technical disciplines (e.g., cloud, artificial intelligence, machine learning, mobile, etc.
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Advanced knowledge of Extract/Transform/Load (ETL) or Extract/Load/Transform (ELT) tools, including both batch and real-time data transmission applications such as SSIS, Informatica, Kafka, Spark, MuleSoft, or equivalent software.
Full-timeExpandApply NowActive JobUpdated 5 days ago - UpvoteDownvoteShare Job
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NET, T-SQL, Azure SQL, Azure Storage, Azure Data Factory, Cosmos DB, GitHub, Azure DevOps, and CI/CD pipelines. Advanced knowledge of multiple programming languages, such as C#, Java, Python, SQL, Scala, or similar.
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Experience with a modern ETL/ELT framework and environment, such as Spark or Databricks. Design and implement robust ELT/ETL data pipelines, including data consolidation, cleansing, transformation/mapping, and storage.
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Integrate Python, AWS services (such as S3 and EMR), Redshift, Snowflake, Hadoop, Hive, Spring, Hibernate, Cassandra, Kafka, and ETL processes into Spark applications. Advanced - Python, AWS, Redshift, Snowflake,Hadoop, Hive, Spring, Hibernate, Cassandra, Kafka, ETL.
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Expertise in Snowflake - data modeling, ELT/ETL using Snowflake SQL, Stored Procs, and knowledge in Big Data areas like Hadoop and Talend (optional) Design, Architecture and implement effective Analytics solutions and models using technologies including, but not limited to - Spark, Hadoop, Snowflake and UNIX.
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Design and build scalable data pipelines using Big Data stack Databricks, Spark Scala, AWS – Athena, S3, Glue ETL, Redshift, Dynamo DB. Any experience with AWS Cloud, AWS Glue ETL, Databricks Delta/Redshift/ Talend Big Data would be added advantage.
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Conduct ETL data integration, cleansing transformations using glue spark script. Skilled in Business Intelligence/Data Warehouse, Data and Technical Architecture, Methodology, Architecture, Data Governance, Data Modeling, ETL Tools, Big Data, Data Lake. Strong expertise applying industry best practice methods and sound enterprise architecture, data architecture/ management, and integration techniques across domains.
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7+ years of experience with tools like Kafka and Spark, Snowflake. Have the ability to facilitate the development of data integration efforts with development team in addition to hands on design and development of large complex ETL jobs.
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Active development of ETL processes using Python, PySpark, Spark or other highly parallel technologies, and implementing ETL/data pipelines. is seeking a experienced Software engineer with focus on Data Engineering, ETL processes, preferably with exposure to both batch and streaming data.
Full-timeExpandApply NowActive JobUpdated 6 days ago - UpvoteDownvoteShare Job
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3+ years of experience in running, using and troubleshooting the ETL Cloudera Hadoop Ecosystem i.e. Hadoop FS, Hive, Impala, Spark, Kafka, Hue, Oozie, Yarn, Sqoop, Flume. Understand Hadoop, Spark, Python and other Eco Systems like Impala, Hive, Oozie, Pig etc., Autosys and UNIX Shell Scripting.
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