MLOPSoffice locations (Pittsburgh, PA, Cleveland, OH, Dallas, TX, Birmingham, AL or Phoenix, AZ,). PNC-ClientTechnical Skills:o Amazon SageMaker: In-depth knowledge of SageMaker, including domain setup, configuration, and infrastructure management.o Cloud Knowledge: A deep understanding of cloud computing concepts, especially related to Amazon Web Services (AWS).o Infrastructure Design: Ability to design and implement MLOPs cloud solutions, considering scalability, security, and performance.o Experience: Practical firsthand experience with cloud MLOps and Data Analytics platforms, preferably AWS SageMaker, Glue, EMR, Athena.o Best Practices: Familiarity with best practices for MLOps and Data Engineering.o EC2 Instances: Understanding of EC2 instance types and their suitability for AWS SageMaker.o S3: Proficiency in using Amazon S3 for data storage and SageMaker input/output.o IAM: Ability to manage permissions and access control using Identity and Access Management.o Lambda: Knowledge of serverless computing for automating tasks.o ML & Data Pipelines: Experience with creating data pipelines using AWS SageMaker services integrated with Glue and EMR.o Monitoring and Troubleshooting: Proficiency in monitoring SageMaker cluster health, identifying bottlenecks, and resolving issues.o Cost Optimization: Strategies to tag SageMaker resources with an eye on optimizing costs and observability.Security and Compliance:o Encryption: Understanding of data encryption at rest and in transit to ensure secure data analytics cloud environment.o Security Groups and VPC: Knowledge of network security and virtual private clouds.o Compliance Controls: Ensuring compliance with industry standards and regulations.Scripting and Automation:o Language Proficiency: Python, R, Spark, SQL in scripting languages for automating tasks.o MLOPs: Ability to collaborate with the business to optimize MLOps process, and model lifeycle using SageMakero Infrastructure as Code (IaC): Ability to assist DevOps engineers to develop proper Terraform templates used to provision AWS analytics infrastructure.Backup and Disaster Recovery:o Snapshotting: Familiarity with taking EMR cluster snapshots for backup and recovery.o High Availability: Implementing strategies for fault tolerance and disaster recovery.Soft Skills:o Communication: Effective communication with stakeholders, developers, and data engineers.o Problem-Solving: Analytical thinking to address complex issues.o Adaptability: Keeping up with evolving technologies and best practices.o Decisiveness: Make informed decisions, especially when dealing with complex architectural choices.o Business Acumen: Understand business requirements and align technical solutions accordingly.o Continuous Learning: A zeal for staying updated with evolving cloud technologies.oExperience and Certifications:o Experience: Senior AWS Cloud Engineers must have 3 to 5 years of firsthand experience in designing and building cloud MLOps and Data Analytics applications.o Certifications: AWS Professional Developer or Data certifications are desired for senior roles