Vehicle Data Analysis Engineer

Business and Engineering Solutions (BES); Brussel; Sur place; EUR 52 000 - 78 000; Plein temps

Résumé du poste

B.E.S. (Business & Engineering Solutions) in Brussels is seeking a Vehicle Energy & Data Analysis Engineer to bridge Powertrain Engineering, energy management and data analysis for BEVs.

You will work on energy consumption, range and SOC prediction, V1G/V2G services using Python, MATLAB, Dataiku and Snowflake, in a multidisciplinary R&D team across international projects.

Qualifications

• Master’s degree in Mechanical, Automotive, or related field.
• Up to 5 years of automotive/powertrain experience.
• Solid BEV and vehicle energy management knowledge.
• Experience with Big Data, data cleaning and analysis.
• Proficiency in Python; MATLAB knowledge; Dataiku and Snowflake are a plus.

Responsabilités

• Develop and maintain data pipelines for energy, range and charging data.
• Clean, structure and analyze large vehicle datasets to identify trends.
• Analyze energy consumption, range and SOC prediction errors.
• Decompose energy consumption into key contributors.
• Collaborate with cross-functional teams on V1G/V2G initiatives.
• Apply Python, MATLAB, Dataiku and Snowflake for processing and modelling.
• Translate analyses into clear conclusions and visualizations.

Connaissances

Python

MATLAB

Data Analysis

Big Data

Data Processing

Dataiku

Snowflake

Vehicle energy management

Formation

Master’s degree in Mechanical Engineering / Automotive Engineering / related field

Outils

Dataiku

Snowflake

Description du poste

About the job

B.E.S. (Business & Engineering Solutions) is growing and is therefore welcoming a new Vehicle Energy & Data Analysis Engineer within an Automotive key player.

As a Vehicle Energy & Data Analysis Engineer, you will operate at the intersection of Powertrain Engineering, Vehicle Energy Management, and Data Analysis, working on data-driven solutions for Battery Electric Vehicles (BEVs).

You will contribute to projects aimed at improving vehicle energy consumption analysis, range prediction, State of Charge (SOC) prediction and smart charging services, using real-world vehicle and cloud data to identify the technical causes behind energy-consumption and prediction errors.

Context:

Join the R&D organization of a major automotive OEM located in Brussels, within a R&D team developing software-based solutions for next-generation electric vehicles.

You will be part of a multidisciplinary team combining Powertrain Engineering, Data Science, Control Engineering and Software Development.

The role focuses on two complementary projects: vehicle energy management and battery/charging-related activities. You will work with large volumes of vehicle and cloud data to understand energy consumption, identify prediction errors, analyse customer driving and charging behaviour, and support the development of V1G (unidirectional smart charging) and V2G (Vehicle-to-Grid) services.

This role is particularly suited to a technical engineer with a strong interest in data and programming. You will have the opportunity to apply your engineering knowledge to real-world vehicle data while developing your expertise in Python, data processing and software-based engineering.

Your Responsibilities:

• Develop, improve and maintain data pipelines to process large volumes of vehicle and cloud data related to energy consumption, range prediction and charging services.
• Clean, structure and analyse large datasets, identifying data quality issues, biases, inconsistencies and relevant engineering trends.
• Analyse real-world and benchmark vehicle data to identify the root causes of range prediction and State of Charge (SOC) errors.
• Decompose vehicle energy consumption into key contributors such as vehicle energy models, driving speed, HVAC/climate consumption and powertrain auxiliary losses.
• Analyse customer driving and charging behaviour to identify relevant customer profiles, use cases and behavioural patterns.
• Support activities related to V1G smart charging and V2G (Vehicle-to-Grid), including monitoring, data analysis and simulation.
• Use Python, MATLAB, Dataiku and Snowflake for data processing, engineering analysis, modelling and simulation, while improving the robustness and scalability of data workflows.
• Collaborate with multidisciplinary and international teams, translating complex technical analyses into clear conclusions, visualizations and recommendations.

Your Profile:

• Master’s of Mechanical Engineering, Automotive Engineering, Electromechanical Engineering, Mechatronics, Electrical Engineering, Powertrain Engineering, or a related technical field.
• Up to 5 years of relevant experience, in the automotive, powertrain, electrification or vehicle engineering, with relevant post-graduate alternance experience also considered.
• Solid technical understanding of BEV, Powertrain systems, vehicle energy management and vehicle energy consumption.
• Experience with Big Data and large datasets, including data cleaning, preparation, quality checks, processing and analysis.
• Comfortable with coding and programming, particularly Python, with a genuine interest in developing data-processing skills.
• Good knowledge of MATLAB for engineering analysis, modelling and simulation; experience with Dataiku and Snowflake is an advantage.
• Understanding of SOC, range prediction, battery systems, charging strategies, V1G, V2G or Smart Charging is highly valued.
• Strong analytical mindset with the ability to perform root-cause analysis, identify energy-consumption contributors and extract meaningful engineering conclusions from data.
• Able to combine technical/engineering knowledge with data and software skills.