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Aws Data Engineer

Pubblicato il 19-10-2026 - Ntt Data Italia in Puglia

Questa posizione è in NTT Data Italia
Il processo di selezione sarà interamente gestito NTT Data Italia.
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Your role as an AWS Data Engineer in NTT Data will be work on AWS Data Platform projects, working in partnership with business analysts and solution architects to understand use cases, data needs, and outcome objectives. In this role, you will deliver data acquisition, transformations and improvement, cleansing, conversion, compression, and loading of data into data lakes in order to be consumed by analytics and machine learning models Your contribution in this role:
- Understand the current application infrastructure and suggest changes to it
- Define and document best practices and strategies regarding application deployment and infrastructure maintenance.
- Migrate our infrastructure with zero downtime to a highly available, scalable one
- Set up a monitoring stack such as CloudWatch, Prometheus, and the ELK stack.
- Define service capacity planning strategies.
- Implement the application’s CI/CD pipeline using the AWS CI/CD stack.




- Write infrastructure as code using CloudFormation or similar.

The ideal profile
- Working experience in a cloud native environment in at least one of the 3 major public clouds (GCP, AWS, Azure), at least 5 year experience on AWS is preferred
- Experience and knowledge of Big Data Architectures, cloud and on premise
- Experience with Docker and Kubernetes. Having used ECS/EKS in the past is a plus
- Experience with the serverless approaches using AWS Lambda
- Strong notions of security best practices (e.g. using IAM Roles, KMS, etc.).
- AWS infrastructure and networking working experience
- Working experience in migrating workloads from on premise to cloud environment
- Experience in monitoring distributed infrastructure, using AWS tools or open source ones such as CloudWatch, Prometheus, and the ELK stack
- Proven experience in: Java, Scala, Python, and shell scripting
- Working experience with Agile Methodology and Kanban
- A

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