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At least 1 year experience with cloud computing (AWS, Microsoft Azure, Google Cloud) Lead Software Engineer, Back End (Go, Python, Java, AWS) Collaborate with digital product managers, and deliver robust cloud-based solutions that drive powerful experiences to help millions of Americans achieve financial empowerment.
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Expert level experience in the areas of design and deployment of VMware VCF, NST-T, vSAN, Azure VMware Solution (AVS), Amazon Web Services (AWS), VMC on AWS, Google Cloud Platform (GCP), Google Cloud VMware Engine (GCVE), VMware Horizon VDI, Citrix Virtual Apps and Desktops, Microsoft WVD / AVD & Amazon Workspaces (VDI.
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Knowledge of distributed computing and cloud services (AWS, Google Cloud Platform, Azure, etc.) Capgemini Engineering has more than 55, engineer and scientist team members in over 30 countries across sectors including Aeronautics, Space, Defense, Naval, Automotive, Rail, Infrastructure & Transportation, Energy, Utilities & Chemicals, Life Sciences, Communications, Semiconductor & Electronics, Industrial & Consumer, Software & Internet.
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We enable organizations of all sizes to easily build, scale, and run modern applications by helping them modernize legacy workloads, embrace innovation, and unleash AI. Our industry-leading developer data platform, MongoDB Atlas, is the only globally distributed, multi-cloud database and is available in more than 115 regions across AWS, Google Cloud, and Microsoft Azure.
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Cloud security certifications like Google Professional Cloud Security Engineer or equivalent are highly desirable. Knowledge of Google Cloud security tools and services such as Google Chronicle and Security Command Center.
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2+ years of experience with AWS, GCP, Azure, or another cloud service. Lead Software Engineer, Back End Do you love building and pioneering in the technology space? As a Capital One Software Engineer, you’ll have the opportunity to be on the forefront of driving a major transformation within Capital One.
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Design and implement cloud security architectures, ensuring the protection of data and applications across cloud platforms (AWS, Azure, Google Cloud, etc. Extensive experience with cloud platforms such as AWS, Azure, or Google Cloud, and their security features.
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Extensive experience with cloud-based ML platforms (e.g., AWS SageMaker, Azure ML, Google Cloud AI). Expert in cloud infrastructure management, including IaC, monitoring, and big data technologies.
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2 years of Experience with a range of architecture tech stacks including Java app servers, Web Servers, Golang, Kubernetes, OpenShift, PCF, AWS, Google Cloud is desirable. Engineer solutions and establish standards for Splunk/ThousandEyes/AppDynamics functional components and specifically agent deployments, including optimizations and application tuning and instrumentation per requirements.
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Strong foundational knowledge across AWS, Microsoft Azure, and/or Google Cloud technology stack. As a Cloud Security Engineer on the Cloud Services team, you will be supporting the creation/communication of our cloud security best practices across all product teams at Morningstar.
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Be informed of developments in ML and network across the Google Cloud ML research community, to provide ASL participants with up to date knowledge and unique opportunities for highly interactive engagements with other Google ML experts.
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We are seeking a seasoned GCP DevOps Engineer with a strong background in Google Cloud Platform (GCP) and Python. Strong experience with Google Cloud Platform (GCP), including big query and cloud storage.
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Proficient in a Cloud stack (AWS, Google Cloud Platform, Azure) and event-streaming technologies (Kafka). KeepStock is in the middle of a digital transformation where it is shifting from an on-premise monolithic architecture to a cloud-based microservices architecture.
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Relevant certifications (e.g., Certified Security - Specialty, Azure Security Engineer, or Google Cloud Professional Security Engineer is a plus. Minimum of 4 years of experience in cloud security, with a strong background in cloud platforms (e.g., AWS, Azure, Google Cloud.
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Strong experience working in cloud environments, with a preference for Google Cloud Platform (GCP) and Microsoft Azure. Experience in cloud computation stacks, including deploying, managing, and scaling AI models is a plus.
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google cloud engineer jobs in Burbank, IL
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