81 architecture "Amazon" positions

AWS Data Engineer (ETL Specialist)

About the Opportunity The AWS Data Engineer is responsible for designing, implementing, and managing the Data pipelines for moving on-premise data to Amazon S3 and Redshift using AWS toolsets

Enterprise Architect

) and storage infrastructures. Knowledge and understanding of Azure and Amazon AWS cloud services infrastructure. Familiarity with at least one common Enterprise Architecture framework, such as TOGAF

Governance, Risk, and Compliance Lead

come in the form of a hosted service (SaaS) and platform (PaaS), utilizing a hybrid architecture, with management services hosted on Amazon Web Services (AWS). Globus capabilities are offered for use with

HPC Cloud Engineer for Computational Chemistry Platform

of applications. Experience in managing cloud databases, such as MongoDB Atlas, Amazon RDS or other managed database services. Experience with Linux operating system, Git and Git Flow. Experience with Jira

Cloud Architect-Enterprise Infrastructure

. Leads the design and architecture of complex cloud solutions in Microsoft Azure, and Amazon Web Services considering performance, availability, security, and cost optimization. 4. Collaborates closely

Data Engineer

we celebrate the successful completion of our digital transformation! Curtin University, a forward-thinking institution, is now leveraging major platforms like Amazon Web Services (AWS), Microsoft, and

Network Engineer

or telecommunications networks (data, voice, video and voice over IP), network architecture, network systems administration, network services and converged network services. May serve as team leader within the work unit

Laboratory Coordinator II

to help coordinate laboratory and field research activities. The focus is on supporting lab activities of the Saleska research group and collaborators at international sites, primarily the Amazon forests

Assist Prof in Next-Generation Approaches of Remote Sensing for Applications to digital soil mapping

networks and deep learning architectures, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), and autoencoders. Experience with data pre-processing, feature extraction, and data

Assist. Prof in Next-Generation Approaches of Remote Sensing for Applications to Digital Agriculture

networks and deep learning architectures, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), and autoencoders. Experience with data pre-processing, feature extraction, and data