Data Engineer - SC Cleared

VIQU IT; Greater London; Presencial; GBP 111.000 - 166.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

SC clearance

2-year contract

Descripción de la vacante

Morela is seeking a data engineer to own the data platform for a UK government programme in Central London. You will design and run end-to-end pipelines, model data with clear schemas, and build RAG retrieval capabilities with secure access controls in an SC environment.

The role focuses on batch and streaming pipelines, data governance, and production-ready data architectures, with a 2-year contract outside IR35.

Formación

• Strong data engineering background with end-to-end pipeline experience.
• Hands-on experience with RAG and retrieval pipelines.
• Experience building pipelines for structured and unstructured data sources.
• Familiarity with data governance, lineage and documentation.

Responsabilidades

• Design, build and maintain robust data pipelines (ETL/ELT) for diverse sources.
• Model data with clear schemas and documentation; ensure data quality and monitoring.
• Develop RAG pipelines including retrieval, chunking, embeddings and hybrid search.
• Implement secure access controls for SC environment and optimise performance.

Conocimientos

Python

SQL

Data modelling

ETL/ELT pipelines

Airflow

Dagster

Spark

Cloud platforms

Docker

Kubernetes

Security governance

Educación

Bachelor's degree in CS/IT/Data Science

Herramientas

Airflow

Dagster

Kafka

OpenSearch

Weaviate

Descripción del empleo

MORELA

AI & Engineering Recruitment

Data Engineer (RAG & Retrieval)

2-year contract | Central London | Active SC | Outside IR35

Morela is supporting a specialist technology consultancy on a 2-year Data Engineer contract in Central London, delivering on a UK government programme. Outside IR35, rate TBC. We need a genuinely strong all-round data engineer first and foremost, with recent hands‑on RAG experience on top. Active SC is essential - eligibility will not be considered.

About the Client

A specialist technology consultancy embedding engineers into SC-cleared government delivery teams. They focus on long-term programme work and give their engineers real ownership of what they build.

The Role

You will own the data platform behind the programme, from ingestion and modelling through to the retrieval layer that powers its AI capability. The core of the job is solid data engineering - reliable pipelines, clean models and well-governed data. On top of that you will build the RAG pipelines that turn large volumes of unstructured material into accurate, access-controlled answers.

Responsibilities

Core data engineering

• Design, build and maintain robust batch and streaming pipelines (ETL/ELT) across structured and unstructured sources
• Model data for analytics and downstream use, with clear schemas, lineage and documentation
• Own data quality, validation, monitoring and alerting so the platform can be trusted
• Optimise pipelines and storage for performance, cost and scale
• Apply security, governance and access controls appropriate to an SC environment

RAG and retrieval

• Build ingestion for unstructured content, including document parsing, OCR and metadata enrichment
• Build production RAG pipelines: chunking, embeddings, hybrid search (vector + BM25), reranking and context assembly
• Enforce document-level access controls at query time
• Evaluate retrieval and generation quality with measurable metrics, and iterate
• Work with self-hosted and open-weight models in secure or air‑gapped environments
• SC clearance: Active SC held, not eligibility

Essential Requirements

Core data engineering

• Strong commercial data engineering background, building and running production pipelines end to end
• Excellent Python and SQL
• Solid grasp of data modelling, warehousing and lakehouse concepts
• Hands‑on with orchestration (e.g. Airflow, Dagster) and distributed processing (e.g. Spark)
• Experience with cloud data platforms (AWS, Azure or GCP) and containerised deployment (Docker, Kubernetes)
• Good engineering practice: version control, CI/CD, testing and infrastructure as code

RAG

• Recent RAG delivery: Hands‑on RAG systems built and shipped recently - current work, not an old proof of concept
• Vector databases (e.g. pgvector, OpenSearch, Qdrant, Weaviate), embeddings, hybrid search and reranking
• Experience evaluating RAG systems properly (e.g. (email address removed), faithfulness)
• Streaming platforms such as Kafka
• Agentic or multi‑hop retrieval, GraphRAG, query rewriting
• vLLM or similar for on‑prem model serving
• LangChain, LlamaIndex, RAGAS or Langfuse
• Government, defence or national security programmes

Working Environment

Central London, SC‑cleared environment, embedded in the programme team. Outside IR35, 2-year contract.