Data Engineer

General role: Contribute to the business value of Data-oriented products based on on-premise Datalake or on cloud environments, by implementing end-to-end data processing chains, from ingestion to API exposure and data visualization General responsibility: Quality of data transformed in the Datalake, proper functioning of data processing chains and optimization of the use of resources of on-premise or cloud clusters by data processing chains General skills: Experience in the implementation of end-to-end data processing chains and Big data architectures in the Cloud (GCP) mastery of languages and frameworks for the processing of massive data in particular in Streaming Mode (Beam DataFlow , Java, Spark / Scala / DataProc). Practice agile methods. Role You will set up end-to-end data processing chains in cloud environments and in a devops culture, You will work on brand new products, for a wide variety of functional areas (Engineering, Connected vehicle, Manufacturing, IoT, Commerce, Quality, Finance), with a solid team to support you. Main responsibilities • During the definition of the project • Design of data ingestion chains • Design of data preparation chains • Design of basic ML algorithms • Data product design • Design of NOSQL data models • Data visualization design • Participation in the selection of services / solutions to be used according to usage • Participation in the development of a data toolbox During the iterative realization phase • Implementation of data ingestion chains • Implementation of data preparation chains • Implementation of basic ML algorithms • Implementation of data visualizations • Use of ML framework • Implementation of data products • Exhibition of data products • Configuration of NOSQL databases • Distributed processing implementation • Use of functional languages • Debugging distributed processing and algorithms • Identification and cataloging of reusable items • Contribution to the evolution of work standards • Contribution and advice on data processing problems During integration and deployment • Participation in problem solving During serial life • Participation in the monitoring of Operations • Participation in problem solving