Data engineer



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Job Description

Position Title: Data Engineer

Date Prepared: July 10, 2024

Position Level: Medior

Location: Hybrid - 2 days in Liège

Condition: Bilingual in French and English required


Job Purpose/Mandate:

As a Data Engineer, you are responsible for translating operational data into a global enterprise data model (EDM) of all company data, supplemented with relevant reference data. The EDM will contain integrated data definitions, impartial to the system or application from which they originate. This is independent of how the data is physically acquired, stored, processed, or accessed. The model will unify, formalize, and represent important concepts as well as the rules that apply to them. The model will be concretely translated into views in a data warehouse and will include both the conceptual design of the data and the efficient storage of the data. The EDM will serve the development of enterprise business intelligence as well as self-service business intelligence.

Specific Duties and Responsibilities:

  • Translate the organization's data strategy and business data requests into coherent BI views (data sets around validated business concepts to support business reporting) that form the EDM.
  • Collaborate with other data engineers to contribute to a conceptual data model that contains all company data to meet data requests as efficiently as possible.
  • Work on project-based data related to a service while also overseeing the entire EDM.
  • Group various business data requests into conceptual business concepts and model the data into BI views.
  • Define and validate business concepts in collaboration with various business stakeholders.
  • Translate business concepts into data elements and code.
  • Ensure clear naming and documentation of different fields in the views (on the data platform and the data catalog).
  • Request data pipelines to the data platform from the IT infrastructure team.
  • Test BI views with the business.
  • Publish BI views.
  • Maintain the integrity of the EDM.
  • Report to the Lead Data Engineer.
  • Interact with the following functions: Business managers/employees, Project managers/employees, Solution architects, Business analysts, Enterprise architect.

Competencies and Qualifications:

Educational Prerequisites:

  • Master's degree with at least 5 years of experience in data modeling.
  • Professional Experience and Skills:
  • Knowledge and experience in Kimball modeling.
  • Excellent knowledge of SQL.
  • Ability to think abstractly and develop conceptual models.
  • Value-oriented with a desire to create value for the business as quickly as possible.
  • Capability to progressively extend the EDM.
  • Experience with Microsoft Azure and Databricks.
  • Experience with modern BI platforms (Cognos, Power BI, Tableau, etc.).
  • Team player.
  • Familiarity with GDPR legislation and its application to the organization of the Data Platform and BI Platform.
  • Communication skills in english and French.

Growth and Skill Enhancement Opportunities:

Technical Skills to Develop:

  • Advanced machine learning techniques.
  • In-depth knowledge of artificial intelligence applications.
  • Enhanced skills in cloud-based data solutions.
  • Expertise in advanced data visualization tools.
  • Continuous integration and deployment (CI/CD) in data engineering.
  • Soft Skills to Develop:
  • Leadership and team management.
  • Advanced problem-solving and critical thinking.
  • Improved project management.
  • Enhanced communication and presentation.
  • Negotiation and conflict resolution.

Role's Contribution to Company Growth:

The Data Engineer’s role significantly impacts the company’s growth by ensuring data integrity and accessibility, which drives informed decision-making, enhances operational efficiency, and supports strategic business initiatives.

Additional Certifications or Training:

  • Certification in cloud platforms (AWS Certified Data Analytics, Google Professional Data Engineer, etc.).
  • Training in advanced data security and privacy regulations.
  • Courses in advanced machine learning and AI.
  • Certification in project management (PMP, Agile, etc.).
  • Participation in workshops and seminars on the latest data engineering trends and technologies.