Leverage various cloud platforms such as AWS, Azure, or Google cloud to build, train, and deploy machine learning models at scale. Cloud Services (AWS, GCP, Oracle.

3-5 or more years of technical or business analyst experience in at least one of the following platforms: Microsoft Azure, Amazon Web Services (AWS), Google Cloud Services, IBM cloud services, other cloud service platforms, VMWare, Hyper-V, Windows Server, Linux, Splunk, FIM, Java, C#, Python, JSON, or SQL.

AWS Solutions Architect Associate or Azure Administrator Associate orGoogle Cloud Engineer Associate. Experience related to AWS, Azure, or GCP technologies such as migration planning, cost optimization, cloud governance etc.

Experience responding to cyber events in public cloud environments such as AWS, Azure, Google Cloud, etc. TCP/IP, DNS, SIEM, and EDR technologies (Splunk, CrowdStrike, Carbon Black, etc.

Experience working with Google Cloud, AWS / AWS AI and ML, AWS Lambda, Amazon Lexbots, and Microsoft Azure. Build and configure demo scenarios in Genesys or NICE CXone Cloud Admin and Architect including ACD, IVR, outbound dialers, queuing, skilling, quality, ACD, Email, Web Messaging, and SMS and other digital channels.

Experience working with cloud infrastructure, AWS, Azure, and/or Google Cloud in particular. Recommended coursework: cloud computing,compilers, database systems, distributed systems, functional PL, machine learning, networking.

Proven experience with public and/or private cloud environments such as Amazon Web Services (AWS), Microsoft Azure, Google Cloud, VMWare ESXi, etc. The SQLES Team is comprised of multiple scrum level teams working towards the same goal: to provide comprehensive, reliable, and scalable solutions for the Teradata SQL Engine (i.e. Teradata Database) for our supported public cloud platforms (AWS, Azure, Google Cloud.

Practical experience with at least one of Microsoft Azure, Google Cloud, or AWS. We work closely with Amazon, Microsoft, Google and other world-class cloud partners to optimise Ubuntu for their infrastructure.

Cloud technology (AWS, Google Cloud) knowledge and experience a plus. Senior Data Analytics Technical Manager/ Data Warehouse. Cloud technology (AWS, Google Cloud) knowledge and experience a plus.

Experience with Google Cloud, AWS or Azure. Configure virtual, cloud-based and cloud-native switching, routing, and firewall settings, protocols, ports, services, access controls, and devices through manual and automated means (scripts, automation and orchestration tools, APIs, etc.

Utilize your in-depth knowledge of mainframe technologies (IBM z/OS, COBOL, JCL, CICS, IMS, DB2) and modern cloud platforms (AWS, Azure, Google Cloud) to guide customers through their digital transformation journey.

7-10 years of data modeling experience with advanced SQL skills and familiarity with various databases, especially cloud platforms like Microsoft Azure, AWS, or Google Cloud.

Experience with other cloud platforms such as AWS, Microsoft Azure, Google Cloud Platform and Snowflake is a plus. This class of SaaS applications is built on the Oracle Cloud Infrastructure (OCI) with data and analytics components like Oracle Autonomous Data Warehouse (ADW), OCI Data Lake, and Oracle Analytics Cloud (OAC.

Experience with cloud infrastructure platforms like AWS, Azure, and Google Cloud. A key feature of the workflows to compose one or more high-performance simulation/AI tasks, streaming Kit-based applications of various types, and elastic microservices via the use of Cloud APIs.

Google Cloud Architect Professional. 5+ years of experience with at least one public cloud provider (AWS, Azure, GCP) Experience with cloud deployments, application modernization, DevOps, SRE,or cloud migrations at Fortune 500 enterprises.