AWS Data Engineer
Pubblicato il 24-09-2026 - Ntt Data in Torino
Job ID: a1J2p000009ipbhEAAPosted: 2026-03-23Location: Milan, Roma, Turin, Pisa, Napoli, Treviso, Cosenza, Bari, Salerno, Bologna, ItaliaSpecialization: AWS Data EngineerWork Modality: Híbrido/FlexibleProcess: a072p00001MNAPHAA5Company: NTT DATAOffer DescriptionYour 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 modelsYour contribution in this role:Understand the current application infrastructure and suggest changes to itDefine 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.RequirementsThe ideal profileWorking 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 preferredExperience and knowledge of Big Data Architectures, cloud and on premiseExperience with Docker and Kubernetes. Having used ECS/EKS in the past is a plusExperience with the serverless approaches using AWS LambdaStrong notions of security best practices (e.g. using IAM Roles, KMS, etc.).AWS infrastructure and networking working experienceWorking experience in migrating workloads from on premise to cloud environmentExperience in monitoring distributed infrastructure, using AWS tools or open source ones such as CloudWatch, Prometheus, and the ELK stackProven