What are the responsibilities and job description for the AWS Cloud Architect position at GreyMatter Solutions?
Job Details
Job Title: AWS Cloud Architect
Job Description:
Client Team is seeking a AWS Cloud engineer to help configure, deploy and operationalize platforms for data science on AWS. As models, apps, and data pipelines are created and operationalized, the data science team requires engineers with understanding of cloud native technology to develop, manage, automate, and facilitate the deployment and operational capabilities of the data science team. AWS Cloud engineer joins a growing competency within the data science team to operationalize a variety of analytics products on cloud platforms.
Responsibilities:
Designing, Configuring, deploying, managing and automating cloud infrastructure (S3, IAM, Redshift, DynamoDB, EC2, VPC, Lambda, CloudWatch, Databricks, Glue, MLops and Athena) that is secure and scalable on AWS to be used by the data science team and extended team.
Monitoring and ensuring the integrity of data pipelines.
Automate Cloud deployments using Terraform.
Administering the deployment, management, and monitoring of applications deployed on AWS via CI/CD and/or containers.
Ensuring the compliance of the data science operations on AWS.
Monitoring usage, cost, and implement optimizations of a variety of AWS resources.
Maintaining the Jenkins pipeline and Perform code promotions through change management
Provision DynamoDB tables with encryption and grant access using the IAM policies
Deploy and manage AWS Serverless application running on API Gateway and LAMBDA
Deploy Redshift Clusters into VPC with encryption, enable cross region snapshots, configure subnet groups and setup monitoring, and resize the cluster using elastic and classic methods
Primary Skills:
AWS: S3, Redshift, DynamoDB, EC2, VPC, Lambda, CloudWatch etc.
Big Data : Databricks, Cloudera, Glue and Athena
Automation: Terraform and Python
Qualifications:
Bachelor's degree with 14 years of experience : 8 years of experience in designing, building, and maintaining AWS Cloud infrastructure and 6 years of experience in Big Data administration and/or infrastructure administration.
Experience in automating AWS infrastructure using terraform and Python is a must.
Experience in database technologies is a plus.
Knowledge in all aspects of DevOps (source control, continuous integration, deployments, etc.)
Proficiency in security implementation best practices on IAM policies, KMS encryption, Secrets Management, Network Security Groups etc.
Experience working in the SCRUM Environment.
Client Team is seeking a AWS Cloud engineer to help configure, deploy and operationalize platforms for data science on AWS. As models, apps, and data pipelines are created and operationalized, the data science team requires engineers with understanding of cloud native technology to develop, manage, automate, and facilitate the deployment and operational capabilities of the data science team. AWS Cloud engineer joins a growing competency within the data science team to operationalize a variety of analytics products on cloud platforms.
Responsibilities:
Designing, Configuring, deploying, managing and automating cloud infrastructure (S3, IAM, Redshift, DynamoDB, EC2, VPC, Lambda, CloudWatch, Databricks, Glue, MLops and Athena) that is secure and scalable on AWS to be used by the data science team and extended team.
Monitoring and ensuring the integrity of data pipelines.
Automate Cloud deployments using Terraform.
Administering the deployment, management, and monitoring of applications deployed on AWS via CI/CD and/or containers.
Ensuring the compliance of the data science operations on AWS.
Monitoring usage, cost, and implement optimizations of a variety of AWS resources.
Maintaining the Jenkins pipeline and Perform code promotions through change management
Provision DynamoDB tables with encryption and grant access using the IAM policies
Deploy and manage AWS Serverless application running on API Gateway and LAMBDA
Deploy Redshift Clusters into VPC with encryption, enable cross region snapshots, configure subnet groups and setup monitoring, and resize the cluster using elastic and classic methods
Primary Skills:
AWS: S3, Redshift, DynamoDB, EC2, VPC, Lambda, CloudWatch etc.
Big Data : Databricks, Cloudera, Glue and Athena
Automation: Terraform and Python
Qualifications:
Bachelor's degree with 14 years of experience : 8 years of experience in designing, building, and maintaining AWS Cloud infrastructure and 6 years of experience in Big Data administration and/or infrastructure administration.
Experience in automating AWS infrastructure using terraform and Python is a must.
Experience in database technologies is a plus.
Knowledge in all aspects of DevOps (source control, continuous integration, deployments, etc.)
Proficiency in security implementation best practices on IAM policies, KMS encryption, Secrets Management, Network Security Groups etc.
Experience working in the SCRUM Environment.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
