About the role
We're looking for a Senior Azure Data Architect for a long-term engagement with an enterprise client. You'll take ownership of an existing Azure data platform, quickly assess and modernise it, and design the data layer behind production GenAI, RAG and Agentic AI applications.
This is not a hands-on LLM or AI-agent development role. What matters is that you have designed, in production, how enterprise data and documents are ingested, prepared, stored, governed and made available for retrieval and AI consumption.
Must-have
- Recent enterprise Azure data architecture experience with clear architecture ownership
- At least one production project (not a POC) where you designed or owned the data layer for a RAG, GenAI or Agentic AI application: document processing, OCR, chunking, embeddings, vector search
- Azure Cosmos DB in depth: data modelling, partition keys, indexing, RU/cost optimisation, Change Feed
- Azure Synapse Analytics, current experience: Pipelines, Spark, Serverless SQL, Dedicated SQL Pools
- Azure Databricks, ADF, Azure SQL MI / SQL Server / T-SQL, ADLS / Lakehouse, Azure Functions
- Strong data modelling (star schemas, fact and dimension tables), metadata-driven ingestion, structured and unstructured data (PDFs, scans, emails)
- Experience taking over and modernising a legacy data platform
- English C1
What you'll do
- Assess an existing Azure data platform, separate quick tactical fixes from the long-term target architecture, and drive both forward
- Deliver implementation-ready architecture: documentation, diagrams and recommendations that engineering teams can act on, with first results within 1-2 weeks
- Design the data and knowledge layer for RAG and Agentic AI applications
- Design scalable metadata/configuration-driven ingestion for databases, APIs and file-based sources
- Make technology-neutral decisions on when Synapse, Databricks, ADF, Azure SQL or a Lakehouse are justified
What we offer
- 12-month full-time contract with a long-term perspective
- Start ASAP