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At least 1 year experience with cloud computing (AWS, Microsoft Azure, Google Cloud) At least 8 years of experience in software engineering (Internship experience does not apply.
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Manage an engineering team responsible for analyzing, designing, programming, debugging, and enhancing software solutions used in various computing environments. Authority in Node.js, Angular, Spring, and Java, applying expertise to drive the development and implementation of data solutions.
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The Department of Information Sciences and Technology (IST) has 44 full-time faculty members with research foci in cybersecurity, data mining and machine learning, natural language processing, human-centered computing, and computing and engineering education.
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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. 1+ years of experience with a public cloud (AWS, Microsoft Azure, Google Cloud.
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As a Cloud Engineer, you will play a critical role in the design, engineering, development, deployment, and use of software for the DOMEX Technology Platform (DTP), where we support our client's mission to centralize and standardize Tasking, Collection, Processing, Exploitation, and Dissemination (TCPED) of Open Source Intelligence (OSINT) across the DoD and IC enterprise.
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Solutions architecture and hands-on engineering/full-stack development of scalable and secure distributed systems using modern software technologies and programming, Cloud Native and microservices architecture, containerization, and API-First design patterns.
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Experience with NetApp, Quantum, and/or Nimble storage products and cloud storage, like AWS EBS, EFS, S3, S3 IA, and Glacier. Computing environment training or certification in Microsoft, Red Hat, NetApp, Quantum, EMC, Nimble, VMware, Brocade, Juniper, or Cisco.
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We use Agile and DevSecOps principles to provide services including application development, biometrics and identity management, cloud and infrastructure optimization, IT and legacy modernization, and data management.
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Basic to substantial experience in one or more of the following commercial/open-source data discovery/analysis platforms: RStudio, Spark, KNIME, RapidMiner, Alteryx, Dataiku, H2O, SAS Enterprise Miner (SAS EM) and/or SAS Visual Data Mining and Machine Learning, Microsoft AzureML, IBM Watson Studio or SPSS Modeler, Amazon SageMaker, Google Cloud ML, SAP Predictive Analytics.
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Experience with cloud-based data warehouses such as Snowflake, BigQuery, or Redshift. This person will have a strong background in data engineering and analytics, with a focus on implementing and optimizing dbt workflows.
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5+ years of experience with architecture and engineering in major cloud services, such as AWS, Azure, or GCP, and with Kubernetes and Terraform. 7+ years of experience in cloud architecture and engineering, including leading cloud solution projects for federal health clients.
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Experience in one or more areas of quantum computing such as algorithm development, quantum error correction, NISQ/hybrid quantum algorithms, quantum machine learning, or quantum error mitigation.
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Preferred Qualification Minimum of 6 years' experience in cybersecurity, including cloud security, compliance, and risk management with a background in system and network security engineering.
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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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Design and support solutions in cloud and virtualized computing environments with and understanding of hybrid cloud architectures. Conduct analysis, design and implementation of infrastructure and cloud data center solutions including computing, networking, routing and security.
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