Job Description :
1. AWS account and GCP project administration experience. a. Includes AWS Organizations and Control Tower experience. b. Includes creating and revising cloud roles and permissions as needed. c. Includes knowledge of using Azure AD SSO for cloud user authentication. 2. Ability to remotely work in a small CCoE core team in Las Vegas. 3. Cost management experience to identify and propose ways to reduce cost where possible. 4. Process and standards development both for within CCoE and for the wider cloud community in the company. a. Includes automation and service configuration to enforce standards where possible. 5. Cloud certifications are obviously a plus. To help with Analytics/AI/ML projects across the company: 1. Data Lake experience: a. AWS Data Lake service and structuring a central data lake for use by multiple business units with overlapping data in some cases. b. Using AWS Glue to process and cleanse raw data uploaded to the data lake into normalized, consistent data in Parquet, csv, and/or Excel format in the data lake. c. Analyzing data lake input objects to identify common schema to merge data from different sources where that makes sense for the business. d. Managing data lake storage using storage tiering, life cycle policies, etc. to reduce cost where possible. e. A plus would be experience with streaming data into the data lake using services like AWS Kinesis 2. Data Warehouse experience: a. AWS RedShift setup and administration. i. Redshift cluster may be used by a number of different business units, especially where their data is similar/related. b. Database schema design. c. Using AWS Glue or other services to load data into Redshift from a data lake. d. Developing DW reports and/or training people how to do it themselves. e. Past experience with more optimal ways to allocate RedShift cost where multiple areas share a common cluster. 3. AI/ML experience: a. AWS SageMaker IDEand related tools. b. Machine Learning model development experience. c. Coordinating data lake source data flowing into AI/ML projects. d. Consulting with AI/ML projects in various business units. 4. Back end data access and reporting infrastructure experience: a. Providing Tableau, Power BI, etc. tools access to processed data stores. b. Triggering events for specific, identified conditions to drive automated actions. To help with cloud migrations, labs, development, etc.: 1. Consulting with areas to develop Infrastructure-as-Code to make deployments repeatable, faster, and with far less time required than on-prem scripted deployments and manual steps. a. Preference is Terraform, but CloudFormation acceptable if workload will always be deployed to AWS. 2. Consulting with areas to develop cloud cost estimates for migrating workloads. (Preference is to POC on cloud to get actual costs where possible 3. Consulting with areas on cloud native technologies and designs to take better advantage of cloud. a. Includes steps for an existing application to reach a more cloud native design over time. b. Includes considering portability where the cloud provider used, or even on-prem in some cases, must vary by deployment based on customer and regulatory requirements. Specific AWS technology experience desired: 1. EC2 2. Lambda 3. AWS Outpost 4. EC2 Image Builder 5. Elastic Kubernetes Service 6. Elastic Container Registry 7. S3 8. EFS 9. AWS Backup 10. RDS (Aurora, SQL Server, PostgreSQL) 11. DynamoDB 12. ElastiCache 13. Database Migration Service 14. VPC 15. CloudFront 16. Route 53 17. API Gateway 18. Direct Connect 19. Organizations 20. CloudWatch 21. CloudFormation 22. CloudTrail 23. Config 24. Trusted Advisor 25. Control Tower 26. AWS Well-Architected Tool (and the framework it supports) 27. AWS Compute Optimizer 28. AWS Proton 29. Athena 30. Amazon RedShift 31. Kinesis 32. QuickSight 33. AWS Glue 34. AWS Lake Formation 35. IAM 36. Resource Access Manager 37. Cognito 38. GuardDuty 39. AWS Single Sign-On 40. Certificate Manager
             

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