Job Description - Data Modeler

Role Overview

Data Edge is looking for an experienced Data Modeler to design, structure, and maintain a Canonical Data Model that supports APIs, integrations, analytics, and future platform development.

The role will focus on translating discovery findings, business requirements, and source system analysis into clear, reusable, and governed data models. The Data Modeler will work closely with data analysts, API engineers, architects, and implementation teams to ensure consistency across entities, definitions, relationships, and metadata.

Key Responsibilities

  • Define conceptual and logical data models based on business discovery findings and technical requirements.
  • Identify and document entities, attributes, relationships, keys, hierarchies, and business definitions.
  • Establish consistent naming standards, data definitions, and modelling conventions.
  • Create, maintain, and evolve canonical entity models to support APIs, integrations, and platform capabilities.
  • Collaborate with Data Analysts, API Engineers, Data Architects, and business stakeholders to validate model design.
  • Support data governance activities, including metadata consistency, business glossary alignment, and data ownership clarity.
  • Translate business concepts into structured, reusable data models for implementation teams.
  • Produce clear model documentation, including ERDs, entity definitions, relationship diagrams, and implementation guidance.
  • Support alignment between source systems, target platforms, APIs, and integration layers.
  • Contribute to data architecture discussions and ensure that models are scalable, consistent, and reusable.

Required Skills and Experience

  • Strong experience in data modelling across enterprise or platform environments.
  • Solid understanding of conceptual, logical, and physical data modelling.
  • Experience creating ERDs and documenting entity relationships.
  • Strong knowledge of entities, attributes, keys, relationships, hierarchies, and business definitions.
  • Experience with canonical data models, enterprise data models, or integration-focused data modelling.
  • Good understanding of data warehousing and data architecture principles.
  • Ability to translate discovery outcomes and business requirements into structured data models.
  • Strong documentation skills and attention to detail.
  • Good communication skills, with the ability to work with business, data, API, and technical teams.

Nice to Have

  • Experience supporting API design, system integrations, or platform modernisation programmes.
  • Familiarity with metadata management, data catalogues, and data governance frameworks.
  • Experience working with data analysts, solution architects, and engineering teams in Agile delivery environments.
  • Understanding of master data, reference data, and reusable enterprise data entities.
  • Experience with modelling tools such as ER/Studio, ERwin, Sparx Enterprise Architect, Lucidchart, or similar.

Profile

The ideal candidate is a structured and detail-oriented Data Modeler who can turn business discovery outputs into clear, reusable, and well-governed data models. They should be comfortable working across business and technical teams and able to create models that support APIs, integrations, analytics, and long-term platform development.

This role is best suited for someone with strong modelling fundamentals, good documentation discipline, and the ability to bring consistency to complex data landscapes.

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