About the role
We’re looking for a Senior Data Architect to join a long-term engagement with an enterprise client. You’ll take ownership of an existing, complex Azure data platform and quickly assess, stabilise and modernise it. You’ll also design the data layer behind 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 knowledge is ingested, prepared, stored, governed and made available for retrieval and AI consumption.
What you’ll do:
Own the architecture of an existing Azure data platform: assess it fast, separate tactical fixes from long-term target architecture, and move both forward in parallel.
Deliver implementation-ready architecture: detailed documentation, diagrams and recommendations that engineering teams can act on. You’ll be expected to show meaningful output within the first 1–2 weeks.
Design the data and knowledge layer for RAG and Agentic AI applications: document processing, OCR and text extraction, metadata, chunking, embeddings, and vector search and retrieval.
Design scalable, metadata- and configuration-driven ingestion for many databases, APIs and file-based sources.
Work with structured and genuinely unstructured data (PDFs, scans, images, emails, free text).
Make technology-neutral decisions about when Synapse, Databricks, ADF, Azure SQL or a Lakehouse are justified, and when they only add complexity.
Improve performance, scalability, maintainability and data quality, including batch, incremental processing and incremental refresh.
Must-have:
Strong, recent experience as an enterprise Azure Data Architect, with clear architecture ownership.
At least one real production project (not a POC) where you designed or owned the data architecture behind a RAG, GenAI or Agentic AI application.
Azure Cosmos DB, in depth (essential): data modelling, partition-key strategy, indexing, RU/throughput and cost optimisation, scaling, consistency, Change Feed, and knowing when Cosmos DB is the right choice and when it isn’t.
Azure Synapse Analytics, current and in depth: Pipelines, Spark, Serverless SQL, Dedicated SQL Pools, and how Synapse compares with Azure SQL, ADF, ADLS, Databricks and Fabric.
Azure Databricks, Azure SQL MI / SQL Server / T-SQL, Azure Data Lake / Lakehouse architecture, and Azure Functions.
Strong data modelling: fact and dimension tables, star schemas, and optimising analytical models.
Proven experience taking over a problematic legacy data platform and modernising it.
Ability to work independently with incomplete information and turn analysis into concrete deliverables quickly.
Fluent English (C1 preferred) and strong communication with both technical teams and business stakeholders.
What we offer:
A 12-month full-time contract with a long-term perspective
A high-impact architecture role at the intersection of enterprise data platforms and GenAI
Fully remote work
A short hiring process: an intro call and a 1-hour technical interview
How to apply
Please send a CV tailored to this role. The client screens CVs strictly and won’t review a generic CV or a list of keywords. For each relevant project, please include:
start and end dates, context, and your personal role and decisions
the Azure services you used (Cosmos DB, Synapse, Databricks and so on) and how you used them
for your RAG/GenAI project: what the application did, what you personally owned, how the data was prepared for retrieval, which storage and vector-search technologies you used, whether Cosmos DB was part of it, and whether it was in production
Please also include:
your expected hourly rate (USD)
your English level
years of experience
your country of residence and your citizenship
your availability date
Shortlisted candidates will be asked to complete a skills matrix.
