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Data Modeler

South HollandHybrid34 hours/week<3months

Data is indispensable for well-functioning systems within a government organization. As a data modeler, you help make data understandable, logical, and usable, ensuring colleagues can access the right information at the right time. You contribute to processes that have a broad impact.

What you will do.

  • You will daily connect data with key business processes.
  • You will create logical and technical data models that show how data relates, for example, for maintenance planning, permits, water levels, or project information.
  • You will work use case-driven: gradually expanding data models based on the information needs of teams.
  • You will pay attention to quality, laws and regulations, and internal standards for data models.
  • You will collaborate with data architects, database administrators, business analysts, application specialists, and data stewards to create models that align with existing systems and future-proof architecture.
  • You will advise clients on their processes and contribute to improvements.

Your activities.

  • Creating and maintaining logical and technical data models based on source data analysis.
  • Translating information needs into clear and usable data models.
  • Correctly applying data standards, guidelines, and laws and regulations.
  • Ensuring proper handover to the line organization and functional management.
  • Supporting clients from various parts of the organization.
  • Collaborating with other data experts to improve interoperability.
  • Contributing to knowledge sharing on normalization, UML/ERD, model types, and reverse engineering.

What they ask

  • Experience in designing and maintaining data models.
  • Knowledge of modeling languages such as ERD and UML.
  • Preferably experience with:
  • Sparx Enterprise Architect and Prolaborate
  • Normalization and reverse engineering
  • Linked Data technology
  • Data lake architectures and Data Vault
  • SQL skills
  • Python

Profile

  • Analytical thinking: translating information needs into clear data models.
  • Collaboration: effectively collaborating with many different colleagues and domains, and communicating with non-technical colleagues in a clear, accessible way.
  • Quality-oriented work: safeguarding standards and identifying areas for improvement.

How to apply

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