Big Data Engineer

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Angajator: ALTEN Romania
  • IT Software
  • Tip job: full-time
    Nivel job: 1 - 5 ani experienta
  • Actualizat la: 26.07.2019
    Scurta descriere a companiei

    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 KEPLER.


    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.

    • 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