We are looking for a person with a combination of data engineer and data scientist skills for a dedicated project. This role is central to transform our approach to forecast the evolution of our customer portfolio and energy demand. The ideal candidate will have a blend of
technical skills (Pyhton, Databricks, Datakiu) and business acumen to refine and implement requirements with our business teams, ensuring our data processes are both efficient and insightful.

Key Responsibilities

1. Work closely with data engineers, data analysts and business stakeholders to
   translate business requirements into data-driven solutions
    
2. Design and implement robust data processing models leveraging
   programming languages and technologies such as Python, PySpark, SQL,
   AWS stack, Databricks, and Dataiku.
    
3. Design and implement data visualization and analytics applications to deliver
   insights and facilitate interaction with business users.
    
4. Lead the transition from Excel-based processes to more sophisticated data
   analysis methodologies, ensuring scalability and reliability.
    
5. Ensure data consistency, accuracy, and quality throughout the data lifecycle.
    
6. Manage and optimize storage, processing, and retrieval systems in terms of
   efficiency and costs.
    
7. Collaborate with Data infrastructure engineers to ensure the scalability,
   security, and performance of the developments done.
    
8. Create and maintain comprehensive documentation for data processes,
   pipelines, and architectures.
    
9. Ensure that data engineering best practices are followed: Code versioning,
   data quality checks, automated pipelines, monitoring and alerting.

Hard skills

Must have

1. Proven experience as a Data Engineer / Data Scientist or in a similar
   role
    
2. Strong programming skills in Python, PySpark, SQL
    
3. Strong problem-solving skills and the ability to work effectively in a
   team-oriented, collaborative environment.
    
4. Experience with Databricks and cloud environments (AWS, Azure)
    
5. Experience with data visualization libraries (Dash, Plotly, Streamlit,
   Bokeh…)

Good to have

1. Ability / interest to work with data science platforms such as Dataiku
    
2. Business knowledge in the utilities industry
    
3. Knowledge of Azure DevOps
    
4. Knowledge of Data warehousing concepts and Data modeling
   techniques (Kimball, DataVault)

Soft skills

• Team player
• Communication skills, especially for explaining technical concepts to
  nontechnical business leaders
• Be adaptable to evolving technologies and changing project requirements.
• Proven organizational skills and attention to detail

Education and professional background

• Bachelor or Master Degree
• 5 years of experience as a data scientist, data engineer or similar position

Languages

• Fluent in either Dutch or French
• Fluent in English