Big Data Architect

Employer: Groupe Renault Romania
  • IT Software
  • Job type: full-time
    Job level: 1 - 5 years of experience
  • Updated at: 22.04.2019
    Short company description

    Grup Renault Romania

    Pasiunea este motorul Grupului Renault. Din pasiune pentru masini si pentru oameni avem astazi in Romania o gama completa de activitati prin care ii oferim fiecarui client vehiculul potrivit. Sa te alaturi Grupului Renault Romania inseamna sa iti poti pune amprenta in oricare dintre etapele de dezvoltare ale unui vehicul: design, proiectare, testare, fabricaţie, logistică, vânzare, post vânzare şi finanţare. Sa faci parte din echipa noastra inseamna sa participi la crearea vehiculului viitorului.


    • Expertise in big data cloud architecture based on managed services or IAAS
    • Depth knowledge of AWS Managed Services
    • Depth knowledge of IAAS infrastructure manipulation on AWS
    • Depth knowledge of deployment automation solutions
    • Knowledge of the general big data ecosystem and the positioning of technologies
    • Knowledge of different big data patterns
    • Expertise in the implementation of end-to-end big data architecture (ingestion / treatment / learning / exhibition of services)
    • Experience with No-SQL databases (column-oriented, key-value, graph) and SQL
    • Strong problem solving, intelligence, initiative and ability to withstand pressure
    • Excellent interpersonal skills and great sense of communication (ability to go into detail)
    • Fluent in English (verbal and written)
    • French are highly appreciated


    Provides Big Data architecture for the solution inline with guidelines, taking into account inputs from Digital Team and stakeholders and maintains it during product lifecycle.

    Key responsibilities :

    • Specifies and maintains Data architecture of the solution that will be developed by data team
    • Ensures product performance, ecosystem integration and flexibility
    • Provides input on any data architecture and data technology issue
    • Ensures data architecture, required capacities and tech alignment between teams maximizing reuse of components

    • During project definition
    - Analysis (actors, flows, volumes, frequencies, types, security, ...)
    - Identification of the data capacity necessary to support the uses
    - Design of the adapted architecture (scalability, resilience, performance ...)
    - Identification of technologies adapted to constraints
    - Complexity management (roadmap)
    - Design of adapted test methods
    - Capitalization on past product architectures
    • During the iterative realization phase
    - Participation in the implementation of innovative cloud solution
    - Strong implication on the validation of the capacities of the solution
    - Contribution and advice on all architectural problems
    • During integration and deployment
    - Contribution to upcoming product architectures
    - Participation in problem solving