Data Engineer - Document & Retrieval Pipelines

Position: Data Engineer - Document & Retrieval Pipelines - Contract
Data Engineer Document & Retrieval Pipelines | SC Cleared Morela is supporting a specialist technology consultancy on a high-profile defence AI programme, and we are looking for a Data Engineer to own the document and retrieval pipelines behind a set of AI-enabled planning tools. This is a contract role on a two-year programme, Outside IR35, based in Central London. Active SC clearance is required.

About the Client Our client is a specialist technology consultancy that embeds engineers directly into government and defence delivery teams. They are known for long-term programme work and for giving their engineers genuine ownership of what they build. This is one of their most strategically important programmes.

The Role You will join a team building AI-enabled planning tools. The core of the role is document and retrieval pipelines: getting messy, real-world documents in, then making them structured, searchable and measurable. The first increment produced working prototypes. The next increment is about building on them to deliver reliable, production-grade services for real end users, so there will be a strong focus on scaling and hardening the pipelines.

You will work as part of a mixed team of engineers, military and civil service colleagues, so being able to represent yourself well and explain technical decisions clearly matters as much as the engineering. Responsibilities
• Build and maintain ingestion pipelines that extract clean text from PDF, DOCX and HTML, including layout-aware parsing of headings, tables and multi-column pages
• Design and build retrieval pipelines for RAG, covering chunking strategy, embedding models, vector search and metadata design
• Own the Postgres layer, including schema design, indexing (including vector indexes) and performance at scale
• Build labelled ground-truth datasets and use them to measure and improve retrieval quality
• Take prototype code to production, hardening pipelines with batching, idempotent re-ingestion and robust error handling
• Containerise services and maintain CI/CD pipelines so changes ship reliably Essential Requirements
• Clearance:
Active SC clearance
• Python:
Strong Python, with experience building and testing data pipelines and APIs (FastAPI, PyTest)
• Unstructured document ingestion:
Extracting clean text from PDF, DOCX and HTML, including layout-aware parsing (headings, tables, multi-column pages)
• RAG retrieval pipelines:
Chunking strategy, embedding models, vector search (Postgres with pgvector or similar) and metadata design
• Postgres:
Schema design, indexing (including vector indexes) and performance at scale
• Retrieval evaluation:
Building labelled ground-truth datasets and measuring retrieval quality
• Product ionising code:
Hardening pipelines (batching, idempotent re-ingestion, error handling), containerisation with Docker and CI/CD with Git Hub Actions

Desirable Experience
• Cloud deployment, particularly Google Cloud; AWS (Bedrock, S3, ECR, EKS) is also used today
• Kubernetes and Helm
• Working with LLM providers (OpenAI, Anthropic, Bedrock) and locally hosted models (Ollama)
• Data labelling workflows (e.g. Label Studio)
• Government, defence or other security-cleared programmes Working Environment Central London, embedded in a mixed programme team with clear delivery milestones. Outside IR35, two-year contract.