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Google Cloud Platform(GCP),SAAS,IAAS. + Cloud Solutions: Microsoft Azure, Amazon Web Confidential (AWS). Bachelors of Science degree in Computer Engineering, Computer Science, Applied Science, Electrical Engineering, or Math.
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Proficiency in designing and managing data pipelines on GCP, using services like BigQuery, Cloud Dataflow, GKE and Cloud Pub/Sub. Certified Google Cloud Engineer, Google Cloud Processional Security Engineer.
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Google Cloud Platform (GCP) cloud is a must, Bigdata or Data Analytics or Data Engineering is a must, Nice to have skills: ELT, DWH, BI. Experience working with infrastructure foundations with GCP will be a huge plus.
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Experience with at least one of the following cloud platforms: Microsoft Azure, Amazon Web Services (AWS), Google Cloud Platform (GCP) - 3-6 years of enterprise-scale technical experience with application portfolios, cloud and hybrid infrastructures for data and analytics, architecture designs, migrations, and technology management.
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Expert in cloud computing platforms and offerings from Microsoft Azure, and Google Cloud Platform (GCP) and experience in writing cloud native application development.
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Develop and implement robust data extraction and transformation processes using GCP tools like BigQuery and leverage Google Colab for collaborative and interactive data analysis. In-depth knowledge of Google Cloud Platform, including BigQuery, and proficiency in SQL.
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A Google Cloud Platform (GCP) cloud engineer needs a variety of skills and experience in order to be successful. Ideally, this person would also possess certification from Google in one or more areas related to their expertise such as Associate Cloud Engineer or Professional Cloud Architect.
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Profound familiarity with Google Cloud Platform (GCP) services. This collaborative approach has convinced both small and large companies, including Calendly, Kung Fu Tea, and Marriott Hotels, to use Designity for their design and marketing efforts instead of traditional, costly, and inefficient alternatives.
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At least 1 year experience with cloud computing (AWS, Microsoft Azure, Google Cloud) 2+ years of experience with AWS, GCP, Azure, or another cloud service. 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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Data mining, statistical analysis, Gaussian, Markov Models, Hierarchical Clustering, K-Means, Linear Regression, Logistic Regression, Monte Carlo Simulation, Neural Networks, deep learning, AI, algorithms, general linear model, GLM, random forest, gradient boosted models, neural networks, optimization, data visualization, Google Cloud Platform, GCP.
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Experience working with cloud-native technologies and environments, such as AWS, GCP, or Azure. Experience with message queue technologies such as Kafka, Google Pub/Sub, AWS Kinesis and delivery semantics such as Exactly-once and At-least once.
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Expertise with Spring Cloud and deploying to cloud platforms (e.g., Pivotal Cloud Foundry, Google Cloud platform) 3+ years of experience building Cloud-enabled solutions (GCP, AWS, PCF.
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Knowledge and experience with any of public cloud providers including Oracle, Amazon Web Services (AWS), Azure or Google (GCP) architecture, tools, and cloud methodologies.
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Google Certified Professional Cloud Architect is preferred but hands-on experience with GCP services using GCP Console is the key. 10+ years of experience in technical solutions implementation, architecture design, evaluation, and investigation in a cloud computing environment preferably Google.
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Experience working with cloud technologies and big data stack be it Amazon AWS, Snowflake, Microsoft Azure or Google GCP. Experience working with cloud technologies and big data stack be it Amazon AWS, Snowflake, Microsoft Azure or Google GCP.
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