Job Description: Cloud Data Engineer (AWS/Azure/GCP | Kubernetes | FinOps)

Position: Cloud Data Engineer

Experience: 912+ Years (can be adjusted based on your requirement)

Employment Type: Full-Time / Contract

Shift: Second Shift (1:00 PM 10:00 PM IST)

Client: US-Based Client

Job Summary:

We are seeking an experienced Cloud Data Engineer with strong expertise in cloud platforms, container orchestration, cloud security, and cost optimization. The ideal candidate will be responsible for designing, implementing, and managing scalable cloud-native data solutions while ensuring high availability, security, and operational efficiency. This role requires collaboration with a US-based client and flexibility to work in the 1:00 PM 10:00 PM IST shift.

Key Responsibilities:

- Design, build, and maintain scalable cloud-native data engineering solutions.

- Develop and deploy data pipelines and cloud-based applications using AWS, Azure, or Google Cloud Platform (GCP).

- Implement and manage containerized applications using Docker and Kubernetes (K8s).

- Deploy and manage microservices and AI/ML model serving environments.

- Design secure cloud architectures with a focus on networking, identity management, and data protection.

- Configure and manage Virtual Private Clouds (VPCs), IAM roles, network security groups, and access controls.

- Ensure data security through encryption at rest and in transit while following Zero Trust security principles.

- Optimize cloud infrastructure costs using FinOps best practices, including auto-scaling, spot instances, and resource monitoring.

- Monitor cloud infrastructure performance, availability, and utilization to improve efficiency and reduce operational costs.

- Collaborate with cross-functional teams to deliver secure, scalable, and high-performing cloud solutions.

- Troubleshoot infrastructure, networking, and deployment issues across cloud environments.

Required Skills & Qualifications:

- Strong experience in Cloud Data Engineering and cloud-native application development.

- Expert-level proficiency in at least one major cloud platform:

1. Amazon Web Services (AWS)

2. Microsoft Azure

3. Google Cloud Platform (GCP)

- Deep understanding of:

1. Serverless Computing

2. Compute Services

3. Cloud Storage Services

- Advanced hands-on experience with:

1. Docker

2. Kubernetes (K8s)

3. Container Orchestration

4. Microservices Architecture

5. Model Serving

- Strong expertise in Cloud Security, including:

1. Virtual Private Clouds (VPCs)

2. Identity & Access Management (IAM)

3. Zero Trust Architecture

4. Encryption at Rest and In Transit

- Experience implementing FinOps practices for cloud cost optimization.

- Strong knowledge of cloud monitoring, logging, and performance optimization.

- Excellent analytical, troubleshooting, and problem-solving skills.

- Strong communication and collaboration abilities.

Preferred Qualifications:

- Cloud certifications (AWS, Azure, or GCP) are highly preferred.

- Experience supporting enterprise-scale cloud environments.

- Familiarity with Infrastructure as Code (Terraform, CloudFormation, or ARM Templates).

- Experience working with CI/CD pipelines and DevOps practices.

- Exposure to AI/ML workloads and model deployment is an added advantage.