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Hands on experience with modern cloud data warehouse and engineering for one or more of the following cloud providers - GCP (Big Query, Vertex, Cognitive Services), Snowflake, Azure (Synapse, Dynamo, Cosmos, Azure ML, Power BI), AWS (Redshift, Sage maker), Tableau;Possessing a certification(s) in one of the following is a big plus – GCP/AWS/Azure/ data or ML engineering.
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Hands-on experience using IaC software tools (CloudFormation, Terraform, Azure Resource Manager, GCP Cloud Deployment Manager etc) and CI/CD tools (IDEs, GitLab, GitHuB, Jenkins, CircleCI, etc.
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Work hands-on with project teams and prospective clients to demonstrate and prototype Google Cloud product integrations in customer/partner environments. You will also collaborate with the product marketing, management and engineering teams to stay on top of industry trends and devise enhancements to the solutions that Publicis Sapient has created with Google Cloud.
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At least 1 year experience with cloud computing (AWS, Microsoft Azure, Google Cloud) 4+ years of experience with a public cloud (AWS, Microsoft Azure, Google Cloud.
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Familiarity with at least one of the following cloud providers: Amazon Web Services (AWS), Google Cloud Compute (GCP), or Microsoft Azure. As a Sr Principal Software Engineer within the Identity Engineering organization, you will be responsible for: identifying, or introducing best practices within the organization; setting technical, and architectural direction across the organization; helping squads, and individuals execute on that direction; and providing subject matter expertise to help accelerate project delivery.
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Understanding or hands on experience with Lex, Nuance Mix, Dialog Flow, AWS and Google Cloud, R, Power BI, Tableau, Alteryx; Applying experience with cloud platforms, such as AWS, Google Cloud, or Microsoft Azure.
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Familiarity with cloud platforms that offer specific support for deploying and scaling generative models, such as Google s Vertex AI, Azure s AI tools, and AWS s Machine Learning services.
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Establish strong software engineering principles for development in Python on the Azure/Google Cloud Platform. Position SummaryAs a Lead ML/AI Engineer, you will drive the design and implementation of functionality related to the end-to-end ML/AI and Feature lifecycle management on Azure/Google Cloud Platform, leveraging and integrating the cloud native services with other standard operational and automation tools.
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Additional cloud-based certifications to credentialize but do not currently meet the rigor of the certification requirement above: CCSP – CCSK – Certificate of Cloud Security Knowledge CCAK – Certificate of Cloud Auditing Knowledge Microsoft Certified: Azure Fundamentals AWS Certified Cloud Practitioner Google Cloud Digital Leader What we look for We’re looking for passionate leaders with strong vision and a desire to stay on top of trends in the risk industry.
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Knowledge of Snowflake, Splunk, Apttus, Docusign, Spring CM, OKTA integration and other cloud solutions. 5+years’ experiencedeveloping industry leading solutions within theAnypointPlatform, including Cloud Hub, On-Prem.
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Role: Java Lead Location: Chicago, Illinois Knowledge/Skills Knowledge in Cloud Architecture (Azure, Google, AWS) to build resilient scalable and maintainable cloud based applications.
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Hands-on experience developing Integrations between Oracle Cloud ERP and other applications. This position will be responsible for the design, development, testing, and delivery of application interfaces between Oracle Cloud ERP and other applications at the University, both on-premise and hosted applications, mostly using MuleSoft as the integration tool.
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Hands-on experience with AWS cloud services: AWS Lambda, AWS Cognito, AWS Amplify, AWS IAM Policies, AWS CloudWatch, AWS API Gateway, AWS S3, AWS Multitenancy, AWS Bedrock, RDS, DynamoDB, and EC2.
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Ability to communicate with a white glove approach to business teamsAdvanced skills with SQL, Power BI, Tableau, or Qlik. Intermediate proficiency with Python (Pandas, Polars, Spark) or R.Experience with Azure Cloud, PowerBI, and Databricks.
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Manage and monitor cloud-based infrastructure (e.g., AWS, Azure, Google Cloud) to ensure high availability and scalability. Strong knowledge of cloud platforms (e.g., AWS, Azure, Google Cloud) and related services.
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