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At least 1 year experience with cloud computing (AWS, Microsoft Azure, Google Cloud) 4+ years of experience with a public cloud (AWS, Microsoft Azure, Google Cloud.
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Experience with provisioning virtual resources and building infrastructures in AWS, Google Cloud, Microsoft Azure, and Digital Ocean commercial clouds. Working knowledge of AWS Cloud Formation, JSON, and Python scripting languages.
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Knowledge of cloud computing technologies such as: Apache Spark, Azure Data Factory, Azure DevOps, Azure ML (Machine Learning), Hadoop, Microsoft Azure, Databricks, AWS, Google Cloud.
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Utilize programming languages like Java, Scala, Python and Open Source RDBMS and NoSQL databases and Cloud based data warehousing services such as Redshift and Snowflake. Center 1 (19052), United States of America, McLean, VirginiaSenior Manager, Data Engineering (Spark, AWS.
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Experience working with cloud technologies (Docker, Kubernetes); Azure / AWS / GCP / OpenShift infrastructure experience. We operate across 30 countries worldwide, offering leading capabilities in digital modernization, AI/ML, Cloud, Cyber and application development.
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Job Description: As a Data Analytics Engineer, you will: Evolve Extract, Transform, Load (ETL) pipelines of structured and unstructured data from a verity of disparate sources to meet the needs of an advanced Insider Threat program.
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Far Ridgeline Engagements LLC (a QinetiQ US Company) is seeking an experienced cloud data engineer/developer to help lead a growing team with a US Department of Defense operations support project developing modern, cloud-based solutions to empower customers to securely store and analyze data.
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Experience with a public cloud, including AWS, Microsoft Azure, or Google Cloud. Experience with distributed data and computing tools, including Spark, Databricks, Hadoop, Hive, AWS EMR, or Kafka.
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10+ years of relevant experience, including data modeling and visualization developing, managing, and exploiting various types of databases ETL assessing data quality and integrity building/maintaining CI/CD pipelines Experience with: Python, SQL, and NiFI AWS or Azure cloud Git/GitHub.
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Experience with cloud platforms such as AWS, Azure, or Google Cloud for deploying machine learning models at scale. We are the "controller" of the Personal Data you provide us and will process any such Personal Data in accordance with applicable law and the statements contained in this Employment Candidate Privacy Notice.
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Demonstrated experience with other non-AWS cloud services such as, Google Cloud Platform, Microsoft Azure. Demonstrated experience with Linux, Python, and cloud CLIs to interact and data in storage and transit.
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Demonstrated experience deploying AWS applications with AWS's Cloud Development Kit (CDK). Move data between different cloud storage environments for critical requests. Certification(s) o AWS DevOps Engineer, Solutions Architect, or SysOps Administrator.
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Experience working with database / data warehouse solutions in cloud (Preferably AWS. Alternatively Azure, GCP). Familiarity with cloud technology, using AWS or Azure.
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Experience in Extract-Transform-Load (ETL) developmentKnowledge of ETL concepts, tools, and data structuresExperience with cloud platforms like Amazon Web Services (AWS), Microsoft Azure, etc.
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5+ years of experience with a public cloud (AWS, Microsoft Azure, Google Cloud) Utilize programming languages like Scala, Java, Python, SQL and GO and NoSQL databases and Cloud based data warehousing services such as Redshift and Snowflake.
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