Azure Data Engineer
Pubblicato il 08-10-2026 - Ntt Data Italia in Milano
Questa posizione è in NTT Data Italia
Il processo di selezione sarà interamente gestito NTT Data Italia.
Questa possibilità è disponibile in Bari - Italy, Bologna - Italy, Cosenza - Italy, Milano - Italy, Napoli - Italy, Pisa - Italy, Roma - Italy, Salerno - Italy, Torino - Italy, Treviso - Italy.
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The Azure Data Engineer in NTT Data knows the challenges of a cloud native environment. Is able to think outside the box finding innovative, yet simple, solutions to every day issues, and share those solutions with the rest of his team. We are looking for an engineer that can be the bridge between Data Science and Data Engineering, having a clear understanding of both worlds. If you are a Data Scientist looking for more experience in preparing data, or a Data Engineer with interest also in Data Science, willing to have a KAIZEN approach, continuously improving technical skills and knowledge, you can be an Azure Data Engineer in NTT Data’s Business Intelligence Service Line,
in an environment where Japanese and European cultural elements are intertwined Your contribution in this role: Your role as an Azure Data Engineer in NTT Data will be supporting customers in Big Data 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. The ideal profile
- Working experience in a cloud native environment in at least one of the 3 major public clouds (GCP/AWS/Azure), 5 years experience on Azure is preferred
- Experience and knowledge of Big Data Architectures, cloud and on premise
- Azure infrastructure and networking working experience
- Experience in building and deliver proofs-of-concept, in order to address specific business needs, using the most appropriate techniques, data s