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Deep understanding of AWS/GCP/OCI cloud services and how to leverage them for compute, storage, and managed services including, but not limited to databases, managed Kubernetes, and Python/Django application services.
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Designing and developing large-scale data solutions using GCP services like DataProc, Dataflow, Cloud Bigtable, BigQuery, Cloud SQL, Pub/Sub, Cloud Data Fusion, Cloud Composer, Cloud Functions, Cloud storage, Compute Engine, Looker, Cloud IAM, etc.
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This Cloud Infrastructure Engineer should have practical experience in administration of Microsoft Azure and other cloud technologies such as GCP. A strong familiarity with compute, network, and storage in Azure, as well as Azure Active Directory, part of Microsoft Entra.
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Minimum 8 years of experience designing, building, and operationalizing large-scale enterprise data solutions and applications using GCP data and analytics services alongside 3rd party tools (Spark, Hive, Cloud DataProc, Cloud Dataflow, Apache Beam/Composer, BigTable, Cloud BigQuery, Cloud Pub/Sub, Cloud Storage, Cloud Functions, & Github.
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This position involves serving as a Subject Matter Expert (SME) within a specific domain such as network, storage, server management, virtualization, O365, Cloud, Monitoring, or Automation. Familiarity with virtualization technologies (VMware, Hyper-V) and cloud services (AWS, Azure, GCP.
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Technologies - IaaS (AWS or Azure or GCP), Databricks platform, Delta Lake storage, Spark (PySpark, Spark SQL). Continuously improve systems through performance enhancements and cost reductions in computing and storage.
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Services that are comparable to Wasabi include AWS S3, Microsoft Azure Blob, and Google Cloud Platform (GCP) Storage. The Wasabi technology stack is deployed as Infrastructure-as-a-Service (IaaS) in top-tier data centers in 6 storage regions in the US, EMEA, and JAPAC. The number of storage regions will increase in the future, as well as the features and packaging options associated with the Wasabi service.
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Web Services (AWS), VMC on AWS, Google Cloud Platform (GCP), Google Cloud VMware Engine (GCVE), VMware Horizon VDI, Citrix. Desktop and Mobility, AWS Solutions Architect Associate, AWS Developer Associate, EMC SE: Enterprise Storage ITIL – Foundation MCSE, A+, N.
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ITIL, ServiceNow); Designing and developing large-scale data solutions using GCP services like DataProc, Dataflow, Cloud Bigtable, BigQuery, Cloud SQL, Pub/Sub, Cloud Data Fusion, Cloud Composer, Cloud Functions, Cloud storage, Compute Engine, Looker, Cloud IAM, etc.
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Expert in cloud computing platforms and offerings from Google Cloud Platform (GCP) (preferred), Microsoft Azure. Data Strategy Requires knowledge of: Understanding of business value and relevance of data and data enabled insights / decisions; Appropriate application and understanding of data ecosystem including Data Management, Data Quality Standards and Data Governance, Accessibility, Storage and Scalability etc; Understanding of the methods and applications that unlock the monetary value of data assets.
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GCP, OCI certifications (a plus) Experience in other integration tools like Talend,Informatica (a plus) Knowledge of services such as Compute Engine, KubernetesEngine, Cloud Storage, Cloud SQL, and BigQuery type technologies Strong problem-solving and troubleshooting skills.
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Relevant hands on experience in the engineering and administration of Microsoft Azure and other cloud technologies such as GCP. Work closely with the Information Security, Engineering and Operations and other cross functional teams in the assessment, design and implementation of robust cloud security solutions across major cloud providers such as Azure and GCP.
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Set Yourself Apart With:Certifications for any of the cloud services like AWS, Snowflake, GCP or AzureExperience working with code repositories and continuous integrationUnderstanding of development and project methodologies.
$99,000 - $148,000 a yearFull-timeExpandApply NowActive JobUpdated 7 days ago - UpvoteDownvoteShare Job
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Knowledge on GCP (Google Cloud Platform) and AWS cloud. Database knowledge: Familiarity with database systems like Oracle or MySQL, PostgreSQL, MongoDB is important for handling data storage and retrieval.
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Experience with GCP data engineering tools (data proc, big query, Google Cloud Storage) and database administration. Experience managing cloud data warehouses (AWS, GCP, Azure) Designing and building a seamless data ecosystem in GCP that allows for agile tables that can provide insights through simple joins.
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