You’ll help make sure data is designed consistently, can be reused effectively and remains easy to understand as the organisation evolves. This includes connecting business definitions with logical and physical data models so that teams can build reliable, well-structured data solutions.Responsibilities
- Business and Domain Discovery - Facilitate identification of key business entities, terminology, ownership and domain boundaries to create a useful map of the data landscape.
- Interaction and Dependency Mapping - Make inputs, outputs, data products, interfaces and cross-domain dependencies explicit before detailed modelling begins.
- Conceptual Data Modelling - Facilitate modelling of business concepts, domains, entities, relationships and key definitions to create a common language across teams.
- Logical Data Design - Produce detailed logical models where they support a clear business or technical purpose, expressing rules, structures, relationships, constraints and definitions independent of technology.
- Physical Data Design Support - Translate logical designs into physical structures suitable for databases, warehouses, lakehouses, streaming platforms, APIs and analytical consumption patterns.
- Data Product and Contract Modelling - Support product teams in designing product schemas, data contracts, semantic layers and reusable datasets that are understandable and fit for consumption.
- Standards and Patterns - Maintain modelling standards, naming conventions, reference data patterns, metadata expectations and reusable templates.
- Metadata and Catalogue Integration - Ensure models are connected to catalogue entries, glossary terms, ownership, lineage, quality rules and governance classifications.
- Model Review and Assurance - Review models for consistency, appropriate normalisation or denormalisation, extensibility, performance implications, privacy, security and change impact.
- Source-to-Target Mapping and Change Impact - Define and validate mappings between source systems, canonical or semantic structures, transformation logic and consuming products, and assess downstream impact of change.
- Change Impact Analysis - Assess how changes to data definitions, schemas and relationships affect downstream products, reports, integrations and controls.
What does success look like?
- Teams share a common understanding of data. Business concepts, definitions, relationships, ownership and domain boundaries are clearly described and agreed across business and technical teams.
- Data designs are traceable and change impacts are understood. Models connect to catalogue entries, definitions, lineage and quality rules, with mappings and dependencies making downstream impacts clear.
- Logical models are clearly reflected in physical models, leading to efficient, consistent data design practices
Your knowledge and experience
- Experience modelling data in Snowflake or a comparable modern cloud warehouse/lakehouse
- Business entity discovery
- Conceptual and domain data modelling
- Interaction, dependency and data-flow modelling
- Logical data modelling
- Physical and dimensional data design
- Canonical and semantic modelling, including shared business measures and definitions
- Data product schema and data contract modelling
- Metadata management, business glossary and data catalogue integration
- Source-to-target mapping and transformation logic
- Strong SQL and data querying capability
- Use of established modelling tools and repositories, with the ability to maintain versioned, reusable artefacts
The type of candidate that we’re looking for:
We’re looking for an experienced Data Modeller who can work across business and technology teams to understand key concepts, relationships and definitions, and turn them into clear, practical models that people can genuinely use. You’ll have experience across conceptual, logical and physical data modelling, with a good understanding of how these support data products, analytics and modern data platforms.
You’ll be naturally collaborative and comfortable working with domain experts, architects, analysts and engineers to build a shared understanding of data across the organisation. Experience with Snowflake or similar cloud data platforms, SQL, data catalogues, metadata, source-to-target mapping and modelling tools will be useful. Above all, we’re looking for someone who can combine attention to detail with a pragmatic mindset, communicate complex ideas simply and create models that remain useful as the organisation evolves.
Critical Skills
- Data Literacy
- Systems Thinking
- Storytelling
- Nurture Relationships
- Team Working
Should you choose to use AI tools to support your application, we ask that you do this thoughtfully. We encourage you to ensure your application reflects your own voice, experience, and motivations. We value authenticity and want to understand your individual strengths and perspectives.
At Baillie Gifford, we are committed to fostering an inclusive and respectful culture in which each of our colleagues can thrive and develop. We believe that our clients are best served by a diverse workforce with the experiences, ideas and perspectives that this brings.
If you are currently working at Baillie Gifford as an employee or contractor please apply to this job from the firm's Workday internal career site.
