Computershare
Data & Knowledge Architect (AI data foundations)
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Data & Knowledge Architect (AI data foundations)
Data & Knowledge Architect (AI Data Foundations)
Computershare, a global leader in financial administration with over 11,000 employees across 22+ countries, seeks a Data & Knowledge Architect for a 12-month contract based in London or Edinburgh. The role is hybrid (3 days per week in the office) and focuses on establishing AI data foundations.
About the Role
Computershare enables financial institutions to optimise investor, employee, creditor, and customer relationships through innovative administration solutions. The company’s global scale ensures robust compliance, risk management, and business continuity—critical for high-stakes organisations.
As a Data & Knowledge Architect, you will design frameworks that transform enterprise data into AI-ready assets, supporting intelligent systems, conversational AI, and advanced analytics across the business.
Key Responsibilities
- Define and enhance the enterprise data architecture, aligning with AI platforms and multi-faceted use cases.
- Design knowledge foundations, including:
- Taxonomies, ontologies, and metadata structures
- Knowledge graphs for AI retrieval and contextual reasoning
- Establish scalable data pipelines for ingestion, transformation, and retrieval—covering both structured and unstructured data.
- Support Retrieval-Augmented Generation (RAG) frameworks, including:
- Embedding strategies
- Vector search optimisation
- Data preprocessing pipelines
- Embed data governance, security, privacy, and Responsible AI principles across the knowledge layer.
- Collaborate with architecture, engineering, and business teams to:
- Ensure data readiness
- Maintain quality and accessibility for AI use cases
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Requirements
Essential
- Strong background in data architecture, knowledge architecture, or data engineering (enterprise-scale).
- Hands-on expertise with AI foundation elements:
- Embeddings (e.g., BERT, Sentence-BERT)
- Vector databases (Pinecone, Weaviate, Milvus)
- RAG frameworks and retrieval mechanisms
- Proven experience driving enterprise-wide transformation programmes, ideally in financial services (an advantage).
- Deep understanding of data governance, quality, lineage, and security in regulated environments.
- Familiarity with modern cloud platforms (AWS/Azure) and associated:
- Data lakes, data warehouses
- ETL/ELT processes
- Cloud-based AI/ML tooling
- Exceptional stakeholder management, with ability to:
- Translate business needs into scalable data/knowledge solutions
- Advocate for governance and engineering best practices
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Next Steps
Computershare commits to merit-based opportunities and an inclusive workplace. Applications are encouraged from diverse backgrounds.
To apply, visit the the link below and speak to one of our Sourcing Specialists.
Note on engagement model:
- This assignment *requires an *Umbrella or PAYE contract (external resource via AMS).
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