Data Engineer
Value Engineer – Data Engineering (AI/Palantir) - hybrid - London £80k-£100k
We're working with a fast-growing, AI-native consulting business that is building production-grade data foundations to power modern AI systems - including knowledge graphs, semantic layers, retrieval systems, and agentic workflows.
This role sits at the heart of that capability. It's not a traditional reporting or BI data engineering position. The focus is on building high-quality, reliable, meaning-aware data pipelines that make AI systems usable, trustworthy, and scalable in real client environments.
What the role is really about
You'll be a senior data engineer responsible for designing and operating data pipelines that don't just move data, but structure it properly - modelling entities, relationships, and constraints so downstream AI systems can reason over it.
You'll work closely with ontology specialists, knowledge graph engineers, and AI engineers to ensure data is semantically aligned, observable, and production ready.
What you'll be doing
- Designing and owning end-to-end data pipelines using Python, SQL, and modern cloud platforms
- Structuring data around real-world concepts (entities, relationships, taxonomies), not just tables
- Building data foundations that support knowledge graphs, retrieval pipelines (RAG), embeddings, and agent workflows
- Implementing data quality, validation, lineage, and observability so pipelines are reliable and trusted
- Collaborating in a consulting-style delivery model, working directly with engineers and client stakeholders
- Creating reusable patterns, documentation, and standards that others can build on
What we're looking for
- Strong senior-level data engineering experience (typically 5–8 years)
- Excellent Python and SQL skills, with hands-on pipeline ownership
- Experience working with cloud data platforms (AWS, Azure, or GCP)
- Exposure to semantic modelling, knowledge graphs, or ontology-aligned data (depth can vary, mindset matters most)
- Comfortable working in ambiguous, client-facing environments with high ownership