Information Architect

The Information Architect will be responsible for defining and governing the information structures, business entities, semantic definitions and logical data models used across D&A domains. The role guides Commerce, Finance, Manufacturing, Supply Chain, Merchandising, Consumer and other data transformations at Pandora by ensuring that information is consistently defined, reusable, discoverable and trusted for analytics, reporting and AI use cases.

In this D&A architecture role, you will define shared information models, create conceptual and logical designs, establish naming and modelling standards, and create information blueprints that engineering teams can implement. Working across commerce, manufacturing and supply chain operations spanning clusters and markets, you will make data easier to understand, govern and consume while supporting Pandora's journey to become the world's leading jewellery company.

Key accountabilities include

• Lead D&A information architecture design, creating semantic, conceptual and logical models that engineering teams translate into Azure Synapse, Databricks and other physical implementations.

• Architect domain information models for commerce (store, consumer, marketing, omnichannel, e-commerce), manufacturing (production, quality, materials) and supply chain (wholesale, inventory, distribution, planning) that reflect business capabilities and operational reality.

• Define information product interfaces and semantic contracts that describe how business entities flow through bronze-to-gold transformations, enabling interoperability between domain-owned data products.

• Develop semantic layer approaches that provide business-oriented abstractions, hiding technical complexity while enabling self-service analytics and trusted AI consumption.

• Co-create master data management strategies for products, customers, suppliers and stores, establishing authoritative sources and harmonisation patterns across systems together with master data responsible teams.

• Establish information quality measures, modelling standards and metadata expectations embedded in architectural patterns: operational schemas in bronze, conformed and dimensional entities in silver, and consumption-ready models in gold.

• Review key physical model proposals from engineering teams, ensuring alignment with D&A information models, semantic definitions, naming conventions and reusable patterns.

• Design information value chains and information product specifications with clear contracts for downstream consumption by analytics and data consumers.

• Map business capabilities to information domains, creating bounded contexts aligned with Domain-Driven Design principles for manufacturing, commerce and supply chain.

• Provide architectural oversight through design reviews and decision records to ensure adherence to D&A data standards, governance requirements and reusable modelling principles.

• Contribute to business glossaries, semantic models and metadata standards that bridge business language and technical implementation, ensuring consistent understanding across technical and business stakeholders.

• Mentor teams on information and data modelling best practices while documenting anti-patterns to avoid common pitfalls in dimensional modelling, semantic inconsistency and naming standards.

• Partner with AI Architecture and Enablement teams to make D&A information assets easier to ground, retrieve and consume in conversational analytics, GenAI and agentic AI solutions.

What is needed to succeed

• 4+ years as a practicing data, information or analytics architect with proven experience designing multi-source, multi-domain information architectures that successfully went into production.

• Demonstrated experience architecting shared information and data models in modern lakehouse patterns, including defining silver-layer conformance standards and gold-layer consumption contracts.

• Practical experience with traditional dimensional modelling (Kimball, Data Vault etc.) and modern data mesh/lakehouse patterns, with ability to guide teams through transitional architectures that harmonise both paradigms.

• Strong semantic modelling capability, including defining business entities, relationships, naming conventions, glossaries and logical models that can be adopted by engineering, analytics and business teams.

• Understanding of Azure data platform capabilities such as Synapse, Databricks, Unity Catalog and Data Factory to guide architectural decisions without becoming the primary owner of…