Data Engineer

ACENSI; Belgique; Sur place; EUR 70 000 - 95 000; Plein temps

Résumé du poste

ACENSI in Brussels is seeking a Data Engineer to join a client in the energy sector. You will develop Python-enabled ML pipelines to forecast energy production for renewable assets such as wind farms and photovoltaic plants, collaborating with data scientists and quants.

The role emphasizes MLOps, feature prep, training, tuning and inference, with strong Python and AWS skills. Databricks, MLFlow and related tools are a plus.

Qualifications

• Python V3 Expert is required.
• Big Data Architecture & Technologies Senior experience.
• Databricks experience is a plus.

Responsabilités

• Forecast energy production using ML models for renewable assets.
• Collaborate with Quants and Data Scientists to set up training pipelines.
• Work with AWS services (S3, Step Functions, Athena) for data processing.

Connaissances

MLOps

Python development

Collaboration with Quants & DataSci

Outils

AWS ecosystem

Databricks

MLFlow

Description du poste

ACENSI is looking for a Data Engineer for one of their clients in the energy sector in Brussels:

We are looking for a passionate python developer to join our team and contribute to the creation of Machine Learning models to forecast the energy production of our renewable assets (wind farms, photovoltaic plants).

The ideal profile is:

• A data engineer who understands the challenges of MLOps (feature preparation, training, tuning, and inference).
• A python development enthusiast, capable of juggling libraries and frameworks.
• A software craftsman capable of working with Quants and Data Scientists to solve problems related to the Machine Learning model lifecycle (e.g., setting up training pipelines).

The position requires advanced proficiency in Python and the AWS ecosystem (s3, step functions, athena, etc...). Previous experience with Databricks, Feature Stores, and Model Registries (MLFlow) is a plus.

Requirements:

• Python V3 Expert (+10 ans)
• Big Data Architecture & Technologies Senior (8 ans < x <= 10 ans)
• Databricks Junior (< 3 ans)
• Esprit d'analyse et de synthèse Senior (8 ans < x <= 10 ans)
• Machine Learning Avancé (5 ans < x <= 8 ans)