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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Principal Data Engineer - **Company:** WTW - **Location:** London, UK - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Data Analysis, Cloud Computing, Code Generation, Continuous Integration, Information Engineering, Data Infrastructure, Data Transformation, Data Security, Software Debugging, Github, Python (Programming Language), SQL Databases, Azure Service Bus, Data Ingestion, Large Language Models, Apache Spark, Data Layers, Data Lakes, Data Lineage, Low Latency, Apache Kafka, Graphql, Data Management, Machine Learning Operations, Virtual Agents, Terraform, Databricks - **Published:** June 18, 2026 - **Apply:** https://uk.indeed.com/viewjob?jk=8e3edfeab0c6a638 ## About the Role Do you have experience in Unity?, * Solid experience in data engineering, with demonstrable depth across platform architecture, data modeling, and production-grade pipeline delivery. * Proven experience building or significantly contributing to a modern data platform at scale - lakehouse, data mesh, or equivalent - serving a large and complex organization. * Track record of setting technical direction and influencing engineering practice beyond your immediate team; you have been the person others look to for the hard calls. * Experience delivering data products that serve diverse consumers - analytics, APIs, AI/ML systems - with different latency, quality, and access requirements. * Background in financial services, insurance, or broking is a plus but not required. Technical Skills * Deep expertise in Databricks, including Unity Catalog, Delta Lake, Delta Sharing, and the full Databricks data engineering and ML stack. * Strong command of DBT for modular, testable, and well-documented data transformation; a clear point of view on semantic modeling and metric layer design. * Fluency in Python and SQL; comfort with Spark for large-scale data processing and transformation. * Experience with modern data ingestion patterns across structured, unstructured, CDC, API, and streaming sources (ADF, Kafka, Event Hubs, or equivalent). * Working knowledge of data contract standards and tooling (e.g., ODCS), and practical experience implementing quality, schema, and SLA commitments in production. * Familiarity with the machine interface layer: APIs (REST, GraphQL), AI agent frameworks, MCP, vectorization, and low-latency query patterns for AI consumption. * Understanding of foundational governance capabilities: access security (Entra ID, Unity Catalog), data lineage tooling, CI/CD for data (Github Actions, Terraform, DBT Cloud), and observability practices. AI Fluency * AI fluency is a core requirement of this role - in two distinct dimensions. First, you will design and build data infrastructure that powers AI-driven products and agent workflows; you need to understand what AI systems require from data and how to deliver it reliably. Second, you are expected to use AI actively in your own engineering practice - for code generation, documentation, debugging, pipeline design, and technical research - treating it as a force multiplier, not a curiosity. * Practical experience integrating LLMs or AI agents with data platforms - whether through RAG pipelines, semantic layers, vector stores, or agentic data access patterns - is a strong advantage. How You Work * You think in systems - you see how individual components connect, where coupling creates risk, and how today's decisions constrain tomorrow's options. * You hold a high bar for engineering quality - correctness, testability, observability, and documentation are non-negotiable, not nice-to-haves. * You are pragmatic under pressure; you know when to build the right thing and when to build the thing that ships, and you are honest about the difference. * You communicate technical complexity with clarity - to engineers, product managers, and senior stakeholders - without losing precision or oversimplifying trade-offs. * You reach for AI instinctively as part of how you work, and you actively share what you learn with the team around you. * You are energized by greenfield scope; you do your best work when you are writing the playbook, not following one. ## Related Videos - [Innovating Developer Tools with AI: Insights from GitHub Next](https://www.wearedevelopers.com/videos/1268-innovating-developer-tools-with-ai-insights-from-github-next) - [Putting the Graph In GraphQL With The Neo4j GraphQL Library](https://www.wearedevelopers.com/videos/257-putting-the-graph-in-graphql-with-the-neo4j-graphql-library) - [Infrastructure as Code: The Developer's Secret Weapon](https://www.wearedevelopers.com/videos/1221-infrastructure-as-code-the-developer-s-secret-weapon) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Bringing AI Model Testing and Prompt Management to Your Codebase with GitHub Models](https://www.wearedevelopers.com/videos/1536-bringing-ai-model-testing-and-prompt-management-to-your-codebase-with-github-models) - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) ## Related Articles - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [What is Software Engineering in the Age of AI?](https://www.wearedevelopers.com/magazine/640-what-is-software-engineering-in-the-age-of-ai)