Big Data Engineer
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Angajator: | ALTEN Romania |
Domeniu: |
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Tip job: | full-time |
Nivel job: | 1 - 5 ani experienta |
Orase: |
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Actualizat la: | 26.07.2019 |
Remote work: | On-site |
ALTEN Romania, part of the international ALTEN Group - with a unique position as Leader in IT & Engineering Consulting, provides support for its clients’ development strategies in the fields of innovation, R&D and IT systems since 1996. The company comprises 2 divisions specialized on its core capabilities: ENGINEERING and IT. These two divisions are: ALTEN TECHNO and ALTEN IT.
Cerinte
General Skills:
Experience in "end to end " data streams implementation and design in Big Data architectures (Hadoop clusters, NoSQL databases, Elastic search) and also in massive data processing environments of distributed data with: frameworks as Spark / Scala.
Mandatory:
• Languages: Spark, Scala, SQL; DevOps: Git, Jenkins, Gitlabee;
• Data lake: NiFi work in distributed architecture; Hortonworks with Hive, Oozie
• Database: NoSQL and SQL
Nice to have:
• Cloud: GCP (Google), AWS
Project methodology it is only Agile/SCRUM, inside a DevOps culture.
Main Responsibilities in different stages:
During project definition:
• Design of data ingestion chains
• Design of data preparation chains
• Basic ML algorithm design
• Data product design
• Design of NOSQL data models
• Design of data visualizations
• Participation in the selection of services / solutions to be used according to uses
• Participation in the development of a data toolbox
During the iterative implementation phase:
• Implementation of data ingestion chains
• Implementation of data preparation chains
• Implementation of basic ML algorithms
• Implementing data visualizations
• Using ML framework
• Implementation of data products
• Exposure of data products
• NOSQL database configuration/ parametrization
• Use of functional languages
• Debugging of distributed processes and algorithms
• Identification and cataloging of reusable entities
• Contribution to the working development standards
• Contribution and solution proposals on data processing issues
During integration and deployment phase:
• Participation in problem solvin
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