English proficiency is mandatory.
Role Overview
We are seeking a highly skilled AWS Cloud Data Engineer to design, build, and maintain scalable, secure, and automated cloud data platforms.
This role will be responsible for developing data pipelines, managing cloud infrastructure, and supporting analytics and machine learning workloads across the AWS ecosystem.
The ideal candidate has hands-on experience with modern AWS data services, Infrastructure as Code (IaC), and distributed data processing technologies, along with a strong understanding of cloud architecture and DevOps best practices.
Key Responsibilities
- Design, develop, and maintain scalable, cloud-native data pipelines using AWS Glue, Amazon Kinesis Data Streams, AWS Lambda, and Amazon S3.
- Build and optimize ETL/ELT workflows using PySpark and AWS Glue.
- Develop, deploy, and support machine learning workflows using Amazon SageMaker.
- Build and manage containerized applications and batch workloads using AWS Fargate.
- Provision, manage, and automate cloud infrastructure using Terraform and OpenTofu, following Infrastructure as Code (IaC) best practices.
- Design and optimize data storage solutions using Amazon Redshift and Amazon S3 to support analytics and reporting workloads.
- Implement and maintain event-driven architectures using Amazon SQS and other AWS messaging services.
- Develop and support secure, automated CI/CD pipelines for application and infrastructure deployments.
- Monitor, troubleshoot, and optimize AWS services to ensure high availability, performance, scalability, and cost efficiency.
- Collaborate with data engineers, software developers, data scientists, and business stakeholders to deliver reliable, end-to-end data solutions.
- Follow cloud security, governance, and operational best practices, including IAM, encryption, logging, and monitoring.