Alexandre Colicchio

Head Of Data Engineering at papernest

Alexandre COLICCHIO has diverse work experience in the field of data engineering and development. Alexandre currently holds the position of Head of Data Engineering at papernest, where they started in January 2022. Prior to this, they worked as a Senior Data Engineer at the same company from August 2021 to January 2022.

Before joining papernest, Alexandre served as a Data Engineer at Liebherr Mining from September 2019 to August 2021. Alexandre also gained professional experience as an Intern Data Analyst at Philip Morris International from February 2019 to August 2019.

In addition to their data engineering roles, Alexandre has experience in development. Alexandre worked as a Développeur Android/IOS (ReactNative) at Lateral Studio Sàrl for a brief period from July 2018 to September 2018. Prior to that, they served as a Développeur Full Stack at IARISS from September 2017 to September 2018, where they undertook various projects related to the field of IT and networks and developed web applications using HTML5/CSS, JavaScript, and created associated APIs and front-end.

Alexandre's earlier experiences include a role as a Junior Android Developer at Oxycar in August 2017 and an apprenticeship as an Apprentice DUT Génie Electrique et Informatique Industrielle at ELECTRO OHMS from August 2014 to August 2016.

Alexandre Colicchio started their education at Lycée Jeanne D'arc, where they received their Baccalauréat in the scientific field in 2012. Alexandre then attended Ecole d'infirmier de la Robertsau from 2012 to 2014. After that, they pursued a DUT par apprentissage in Génie Electrique et Informatique Industrielle at IUT De Mulhouse from 2014 to 2016. Subsequently, Alexandre studied at Ecole Nationale Supérieure d'Ingénieurs Sud Alsace, obtaining their Diplôme d'ingénieur in Informatique et réseau between 2016 and 2019. Finally, they attended EPFL (École polytechnique fédérale de Lausanne) from 2018 to 2019, where they completed their Master 2 (M2) degree in Machine Learning & Big Data.

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