We are seeking a highly motivated and detail-oriented Cloud Engineer to join our Powertrain Data and Automation team. The ideal candidate will have experience in deploying microservice architectures in AWS, managing hybrid on-premises and cloud-based data and service deployments, and building resilient and scalable data infrastructure. This is an exciting opportunity to work on cutting-edge cloud technologies and gain valuable experience in a fast-paced and innovative environment.

Responsibilities

Design, implement, and maintain microservice-based architectures within AWS. Manage hybrid deployments of data and services across on-premises and cloud environments. Develop and optimize resilient and scalable data infrastructure to support big data initiatives. Utilize and manage AWS services such as S3, VPC, EKS, Kubernetes, EC2, and Auto Scaling to deliver reliable solutions. Implement Infrastructure as Code (IaC) using tools like CloudFormation templates or other IaC languages. Develop, deploy, and maintain alerting systems to ensure high availability and performance using CloudWatch and other monitoring tools. Develop, standardize, and contribute to DevOps processes, including CI/CD pipelines and GitLab Runners. Leverage the Elastic Search stack (ELK) with tools like Filebeat, Metricbeat, and Logstash for observability and log management. Deploy and maintain unit and integration tests to ensure system reliability and performance.

Qualifications

3-5 years of experience in a cloud engineering role. Proven experience deploying microservice architectures in AWS. Experience working with hybrid on-premises and cloud-based deployments. Hands-on experience with big data technologies and implementing scalable data infrastructure (spark, iceberg, kafka, airflow). Proficiency in relevant tools and platforms including AWS S3, VPC, EKS, Kubernetes, EC2, Auto Scaling, CloudWatch, and CloudFormation templates. Familiarity with DevOps practices and CI/CD tools such as GitLab Runners. Understanding of the Elastic Search stack (ELK) and associated tools like Filebeat, Metricbeat, and Logstash. Experience with monitoring and alerting platforms. Knowledge of unit testing and integration testing best practices.

Education

Bachelor's degree in Computer Science or a related technical field, or equivalent practical experience. CKA (Certified Kubernetes Administrator) strongly preferred CKAD (Certified Kubernetes Application Developer) strongly preferred.

Nice to Have

Experience working with manufacturing data and infrastructure, particularly in the automotive sector. A strong understanding of industry-specific challenges and requirements in manufacturing environments. Hands on experience designing and building End to End data solutions and platforms.