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Experience working with cloud technologies (Docker, Kubernetes); Azure / AWS / GCP / OpenShift infrastructure experience. 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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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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Preferred Skills: Knowledge of cloud platforms such as AWS, Azure, or Google Cloud. As a Data Engineer, you will play a crucial role in designing, developing, and maintaining our clients data infrastructure.
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Certification in cloud platforms (e.g., Azure DevOps Engineer Expert, AWS Certified DevOps Engineer). Experience with cloud platforms (e.g., Azure, AWS, GCP.
$143,706 a yearFull-timeRemoteExpandApply NowActive JobUpdated 3 days ago - UpvoteDownvoteShare Job
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Experience with provisioning virtual resources and building infrastructures in AWS, Google Cloud, Microsoft Azure, and Digital Ocean commercial clouds. Position Overview 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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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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5+ years of experience implementing modern designs using at least one cloud-based solution/platform (AWS, Azure, GCP) Advanced level proficiency with at least one ETL / Data Orchestration technology (Azure Data Factory, SSIS, Informatica, Alteryx, Ab Initio, Pentaho, Talend, Matillion.
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Experience with a public cloud (AWS, Microsoft Azure, Google Cloud) Building required infrastructure for optimal extraction, transformation and loading of data from various data sources using AWS and SQL technologies.
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Experience with distributed data platforms and technologies (e.g., Hadoop, Spark, Kafka) and cloud-based data services (e.g., AWS, Azure, GCP) Certifications related to data engineering or cloud platforms.
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Experience with development in cloud environments such as AWS, Azure, Google Cloud. Propose ways to improve efficiency, data quality, and scalability of the ETL process, propose and/or implement new technology including AI/ML that can be used to automate data engineering tasks and processes.
$216,000 a yearFull-timeExpandApply NowActive JobUpdated 6 days ago - UpvoteDownvoteShare Job
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We operate across 30 countries worldwide, offering leading capabilities in digital modernization, AI/ML, Cloud, Cyber and application development. 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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Hands-on experience deploying and operating applications using IaaS and PaaS on major cloud providers, such as Amazon AWS, Microsoft Azure, or Google Cloud Services. The Data Scientist /ML Engineer will work directly with data scientists, software engineers, and subject matter experts in the definition of new analytics capabilities able to provide our federal customers with the information they need to make proper decisions and enable their digital transformation.
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Maintain a deep understanding of cloud computing platforms (e.g., AWS, Azure, Google Cloud). The Leidos Digital Modernization Sector is seeking an experienced Sales Engineer to provide hands on technical expertise with repeatable offerings (RO’s) within the Cloud and Data Center Practice Area at our Leidos Headquarters in Reston, VA.
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In depth knowledge with one or more cloud providers (e.g., AWS, Oracle, IBM, Azure and GCP) and experience working across environments and on premise. Assist with the implementation of data migration/pipelines from on-prem to cloud storage platforms.
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Ability to work with cloud-based data technologies (AWS, Azure, Google Cloud). The Data Engineer will be responsible for developing, constructing, testing, and maintaining data architectures, such as databases and large-scale processing systems.
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azure aws cloud jobs Title: data engineer in Herndon, VA
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