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C2C : AWS Cloud Engineer at Minneapolis, MN

Job in Minneapolis, Hennepin County, Minnesota, 55400, USA
Listing for: Tech Mirrors
Full Time position
Listed on 2026-06-19
Job specializations:
  • IT/Tech
    AWS, Cloud Computing: Infrastructure & Operations
Salary/Wage Range or Industry Benchmark: 100000 - 140000 USD Yearly USD 100000.00 140000.00 YEAR
Job Description & How to Apply Below
Position: Now C2C Hiring : AWS Cloud Engineer at Minneapolis, MN

Role – AWS Cloud Engineer

Location – Minneapolis, MN (Onsite)

Job Type – C2C/W2

Need Local Candidate

Job Description

Minimum 10+ years of experience.

7+ years of experience in cloud engineering, with at least 4+ years of hands‑on AWS experience.

  • AWS Data Sync
  • Amazon S3 (replication, lifecycle policies, versioning, encryption)
  • AWS Sage Maker – 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 (Cloud Formation, Terraform, or equivalent)
  • Solid understanding of IAM, encryption (KMS), and AWS security best practices
  • Ability to architect solutions, not just operate them
  • 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, Data Sync, S3 Replication, Sage Maker, 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 Data Sync 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 Sage Maker, 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
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