The company is a specialist AI and data consultancy focused on implementing intelligent enterprise systems across multiple industries, particularly in financial services and banking. We seek a Data Modeler to lead the modernization of enterprise data ecosystems, bridging low-level data engineering and high-level decision intelligence. Your primary objective will be to design and implement scalable data models and semantic layers within Lakehouse architectures, creating robust Knowledge Graphs and Ontologies for advanced data discovery and interoperability.
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Your responsibilities as the Data Modeler will include:
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Data Modeling
- Design conceptual, logical, and physical data models for Medallion architecture (Bronze, Silver, Gold layers).
- Implement dimensional modeling for analytical layers.
- Apply Slowly Changing Dimensions (SCD2) and historical tracking techniques.
- Define and enforce naming conventions, metadata standards, and maintain model documentation.
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Semantic Layer & Ontologies
- Design and implement a semantic layer for business-friendly data access and self-service analytics.
- Work with advanced AI-tooling for semantic layer deployment and integration.
- Develop and maintain ontologies and taxonomies to standardize business concepts across domains.
- Ensure semantic consistency across data products and reporting layers.
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Knowledge Graph Development
- Build and maintain knowledge graphs to represent relationships between entities and enable advanced data discovery.
- Integrate knowledge graph capabilities with Lakehouse metadata and lineage tools (e.g., OpenMetadata).
- Collaborate with architects and platform engineers to ensure graph scalability and performance.
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Collaboration & Governance
- Work closely with Data Architects to align models with Lakehouse design principles.
- Partner with Data Engineers to ensure models are correctly implemented in Glue and Iceberg tables.
- Collaborate with Data Quality teams to embed validation rules and ensure compliance.
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Optimisation & Standards
- Ensure models support schema evolution, partitioning strategies, and performance optimisation.
- Create reusable modeling templates and best practices for Data Factory squads.
Requirements
To be successful in this role, you should have:
- Strong experience in data modeling for Lakehouse or data warehouse environments.
- Proficiency in semantic layer design, ontologies, and knowledge graph development.
- Familiarity with AWS Glue, Apache Iceberg, and Medallion architecture.
- Understanding of metadata management and lineage tools (OpenMetadata preferred).
- 7+ years in data modeling or data architecture roles.
- Experience in semantic technologies, knowledge graphs, and financial services domain is a strong plus.
You will also have experience in:
- Data modeling tools (ERwin, PowerDesigner, or similar).
- Semantic layer tools (e.g., Zaimler, AtScale, or equivalent).
- Knowledge graph frameworks (e.g., RDF, OWL, Neo4j, or similar).
- Analytical and conceptual thinking.
- Communicating and stakeholder engagement abilities.
- Working in a fast-paced environment and delivering aggressive migration targets.
- Collaborating and communicating with different levels of stakeholders.
- Working with Jira and agile methodologies.
Benefits
- Competitive salary and performance bonuses
- Comprehensive health insurance
- Professional development and certification support
- Opportunity to work on cutting-edge AI projects
- Flexible working arrangements
- Career advancement opportunities in a rapidly growing AI company
This position offers a unique opportunity to shape the future of AI implementation while working with a talented team of professionals at the forefront of technological innovation. The successful candidate will play a crucial role in delivering transformative AI solutions to our clients.
