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We are seeking a Senior AWS Cloud Engineer with deep hands-on experience in architecting, implementing, and migrating large-scale data solutions on AWS. This role focuses on on-premises to AWS data migration, large data storage architectures, and enterprise-grade data transfer solutions using AWS DataSync, S3 replication, and related AWS services. The ideal candidate will lead technical design, implementation, and optimization efforts while working closely with architecture, infrastructure, and security teams.
Key Responsibilities
Design and implement scalable, secure, and cost-optimized AWS data storage architectures for large datasets.
Configure and manage AWS services including EC2, S3, RDS, Lambda, VPC, IAM, Route 53, DataSync, S3 Replication, SageMaker, Glue, ELB, FSx, ECR, and Secrets Manager.
Lead on-premises to AWS cloud data migration initiatives, including planning, execution, validation, and cutover.
Architect and configure AWS DataSync for high-volume, reliable data transfers between on-prem systems and AWS.
Implement and manage Amazon S3 replication (CRR/SRR), lifecycle policies, encryption, and access controls.
Design and develop machine learning models using AWS SageMaker, integrated with Jupyter Notebook, to enable scalable model training, evaluation, and deployment.
Design solutions for large data ingestion, archival, backup, and disaster recovery using AWS services.
Perform hands-on implementation of AWS infrastructure using best practices and Infrastructure as Code (IaC).
Implement CI/CD pipelines using Jenkins or similar tools.
Optimize data transfer performance, storage costs, and data durability.
Collaborate with application, database, network, and security teams to ensure seamless integrations.
Troubleshoot and resolve complex data migration and storage issues.
Enforce AWS security, governance, and compliance standards for data protection.
Required Qualifications
7 years of experience in cloud engineering, with at least 4 years of hands-on AWS experience.
Strong hands-on experience with:
AWS DataSync
Amazon S3 (replication, lifecycle policies, versioning, encryption)
AWS SageMaker
Large-scale data storage and migration
Proven experience migrating terabytes to petabytes of data from on-premises environments to AWS.
Strong understanding of networking concepts (VPN, Direct Connect, bandwidth optimization).
Experience designing high-availability, fault-tolerant cloud architectures.
Hands-on experience with Infrastructure as Code (CloudFormation, Terraform, or equivalent).
Solid understanding of IAM, encryption (KMS), and AWS security best practices.
Ability to architect solutions, not just operate them.
Role Descriptions: AWS devops engineer to build deployment pipeline and automatte
Essential Skills: AWS devops engineer to build deployment pipeline and automatte
Desirable Skills:
Keyword:
Skills: AWS DevOps and Automation
Experience Required: 6-8
We are seeking a Senior AWS Cloud Engineer with deep hands-on experience in architecting, implementing, and migrating large-scale data solutions on AWS. This role focuses on on-premises to AWS data migration, large data storage architectures, and enterprise-grade data transfer solutions using AWS DataSync, S3 replication, and related AWS services. The ideal candidate will lead technical design, implementation, and optimization efforts while working closely with architecture, infrastructure, and security teams.
Key Responsibilities
Design and implement scalable, secure, and cost-optimized AWS data storage architectures for large datasets.
Configure and manage AWS services including EC2, S3, RDS, Lambda, VPC, IAM, Route 53, DataSync, S3 Replication, SageMaker, Glue, ELB, FSx, ECR, and Secrets Manager.
Lead on-premises to AWS cloud data migration initiatives, including planning, execution, validation, and cutover.
Architect and configure AWS DataSync for high-volume, reliable data transfers between on-prem systems and AWS.
Implement and manage Amazon S3 replication (CRR/SRR), lifecycle policies, encryption, and access controls.
Design and develop machine learning models using AWS SageMaker, integrated with Jupyter Notebook, to enable scalable model training, evaluation, and deployment.
Design solutions for large data ingestion, archival, backup, and disaster recovery using AWS services.
Perform hands-on implementation of AWS infrastructure using best practices and Infrastructure as Code (IaC).
Implement CI/CD pipelines using Jenkins or similar tools.
Optimize data transfer performance, storage costs, and data durability.
Collaborate with application, database, network, and security teams to ensure seamless integrations.
Troubleshoot and resolve complex data migration and storage issues.
Enforce AWS security, governance, and compliance standards for data protection.
Required Qualifications
7 years of experience in cloud engineering, with at least 4 years of hands-on AWS experience.
Strong hands-on experience with:
AWS DataSync
Amazon S3 (replication, lifecycle policies, versioning, encryption)
AWS SageMaker
Large-scale data storage and migration
Proven experience migrating terabytes to petabytes of data from on-premises environments to AWS.
Strong understanding of networking concepts (VPN, Direct Connect, bandwidth optimization).
Experience designing high-availability, fault-tolerant cloud architectures.
Hands-on experience with Infrastructure as Code (CloudFormation, Terraform, or equivalent).
Solid understanding of IAM, encryption (KMS), and AWS security best practices.
Ability to architect solutions, not just operate them.
Role Descriptions: AWS devops engineer to build deployment pipeline and automatte
Essential Skills: AWS devops engineer to build deployment pipeline and automatte
Desirable Skills:
Keyword:
Skills: AWS DevOps and Automation
Experience Required: 6-8