Data Modeller; Sizewell C)

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At Sizewell C, we're building more than a nuclear power station—we’re creating a lasting legacy of clean energy and innovation.

To help achieve this, we’re seeking a Data Modeller to design and develop the enterprise-level data models that enhance the data accessibility, usability and value across the organisation. Working alongside Data Architecture Lead, helping to define, build, and deliver data models that align with our strategic business needs and drive informed decision-making.

Contract Type:
Permanent - Office-based with hybrid flexibility (typically 3 days p/w in the office)
Working Pattern:
Full time

Location:

London
Salary:
Circa £60,000 - £65,000 depending on experience
Bonus: 5% annual incentive
Pension:
Up to 7.5% employee contribution / 15% employer contribution
Holiday: 28 days plus bank holidays
Benefits:
Flexible benefits
Closing Date: 22nd October 2026

As a Data Modeller, you’ll help to design the various layers of data models to align with the SZC standards and principles for all domains and sub-domains within SZC. Work alongside with Integration and Engineering team to ensure all source requirements are captured and support the implementation of data models being created.

• Design and develop conceptual, logical, and physical data models to support business intelligence, analytics, and operational systems.
• Collaborate with stakeholders to gather and analyse data requirements.
• Translate business requirements into data structures that are efficient, scalable, and maintainable.
• Enforce data modelling standards, best practices, and governance.
• Work with data engineers to implement models in data warehouses, data lakes, and other storage systems.
• Maintain and update data models as business needs evolve.
• Ensure data integrity, quality, and consistency across systems.
• Document data models, metadata, and data dictionaries.
• Support data lineage and impact analysis efforts.
• Conceptual Data Models:
  High-level models that outline business entities and relationships.
• Logical Data Models:
  Detailed models that define data elements, attributes, and relationships without considering physical implementation.
• Physical Data Models:
  Implementation-ready models tailored to specific database technologies, including indexing, partitioning, and storage details. Also ensure that models are aligned to respective layers.
• Meeting notes, requirement gathering documents, and stakeholder feedback summaries.
• Comprehensive documentation of data elements, definitions, data types, and business rules.
• Metadata repositories that support data governance and discovery.

• Visual representations of data entities and their interrelationships, used for communication with stakeholders and developers for each domain/sub-domain/data products depend on requirements.
• Assessments of how changes in data models affect downstream systems, reports, and processes.
• Contributions to data architecture blueprints and alignment with enterprise data strategies.
• Managed and versioned models stored in tools like ERwin.

• Mapping between source systems and target models, especially for ETL/ELT processes.
• Mapping between target models and Semantic models.

Documentation of naming conventions, modelling standards, and best practices to ensure consistency across the organization need to be enforced..

We’re interested in hearing from candidates who have experience in the following areas:

• Experience With different data modelling techniques to define…