Senior Full Stack Software Development Engineer in London

Bloomberg runs on data. Every product, model, chart, alert, workflow, and client-facing insight depends on engineers being able to find, understand, trust, and use financial datasets at scale. DataHub is Bloomberg's experience layer for data. What GitHub is for code, DataHub is for data: the place where engineers discover datasets, understand schemas, request access, publish streams, subscribe to changes, query data, and build data-driven applications.

We are looking for engineers who can imagine the future data experience - and then build the full stack required to make it real. This is a senior full-stack engineering role at the intersection of product experience, distributed systems, developer platforms, data infrastructure, and AI-ready metadata. You will help design and build the next generation of DataHub: the interfaces, backend services, and control-plane systems that allow Bloomberg engineers to move from intent to outcome — from finding the right dataset to understanding it, accessing it, provisioning infrastructure around it, querying it, publishing it, and operating it safely in production.

This is not only a frontend role, and it is not only a backend infrastructure role. The next frontier is AI. For agents to be effective with data, they need more than raw tables and APIs. They need context: catalog metadata, schemas, lineage, ownership, quality signals, permissions, relationships, usage patterns, and business meaning. We are building the semantic and experiential foundation that will allow both humans and AI agents to understand and work with Bloomberg's data safely. It is about designing a new human-and-agent experience for Bloomberg's data universe.

Responsibilities include:

• Build intuitive, production-grade product experiences for engineers working with data.
• Design and implement full-stack workflows across React-based interfaces, APIs, and backend services.
• Build control-plane systems that turn complex data infrastructure into simple, reliable user actions.
• Apply design thinking to technical workflows: understand user pain points, prototype better experiences, and turn strong ideas into production software.
• Shape experiences around data discovery, cataloging, schema understanding, semantic context, lineage, and AI-assisted workflows.
• Help create new data experiences across portals, notebooks, query tools, programmable workflows, and agentic interfaces.
• Work with engineers across Bloomberg to understand how they use data and turn recurring friction into platform capabilities.

Qualifications:

• Strong professional software engineering experience building production systems.
• Experience building reliable frontend applications using React, Vue, or a similar modern UI framework.
• Backend engineering experience in Java, Kotlin, Scala, Go, or another production backend language.
• Strong systems fundamentals across distributed systems, Linux, networking, APIs, service reliability, or data infrastructure.
• Experience owning features or services end-to-end, from design and implementation through rollout and operation.
• Product-minded engineering judgment: the ability to translate ambiguous user needs into intuitive, reliable software experiences.
• A degree in Computer Science, Engineering, Mathematics, or equivalent practical experience.
• Experience building developer platforms, internal tools, control planes, data platforms, cloud platforms, or engineering productivity products.
• Familiarity with data catalogs, metadata platforms, semantic layers, lineage systems, knowledge graphs, or search and discovery experiences.
• Experience applying design thinking, prototyping, user research, or developer-experience principles to technical platforms.
• Interest in AI-assisted developer workflows, agentic systems, semantic search, data discovery, metadata management, or data infrastructure.
• A track record of taking ambiguous ideas and turning them into polished, production-quality software.

This role is about more than building infrastructure. It is about shaping how engineers experience data. It is designing the right abstractions, workflows, and interfaces so that powerful data infrastructure becomes simple, trustworthy, and useful. Prior experience with semantic technologies, data catalogs, or knowledge graphs is helpful, but not required. DataHub is where Bloomberg's data becomes discoverable, understandable, usable, programmable, and operational.