Job Description

We are looking for an ambitious Data Engineer to join our R&D team. Your role will mainly consist of creating and elaborating data pipelines (ETL/ELT) responsible for collecting, transforming and validating data for our new GlobLearn. This job offers you the unique opportunity to build a future-oriented application that can make Supply Chains more efficient through artificial intelligence (AI), more specifically, Federated Learning. You will play a key role in developing a secure environment where each participant stores their own data locally via a Data Vault, but can still contribute to training collaborative machine learning models.

Your Responsibilities:

• Design and implement ETL pipelines and data pipeline orchestration to process data efficiently and securely.
• Complete and elaborate the project’s architecture where necessary. This means you will have to make your own choices about the design and implementation of the project.
• Getting in touch with machine learning (Federated Learning) tools.
• Collaborate with other developers and stakeholders to build a user-friendly, secure and scalable solution.

Globis is an innovative software company that develops and implements ERP, WMS and TMS solutions at medium-sized companies. Globis is investing significantly in R&D and has developed a Proof of Concept for a new product called GlobLearn, which will enable ‘Federated Learning’ in supply chains. With this, we aim to enable logistics companies -who collaborate horizontally in supply chains- to train machine learning models (such as ETA prediction) without having to make their data public to others in the chain.