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Salary
≈ $106k – $206k per year (Estimated)
Location
In office (London)
Seniority
Senior
Visa
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Confirmed on the employer's own hiring board on Oct 31, 2026. First seen by Alion on Sep 10, 2026. Bloomberg scores A on the Alion truth index.

Overview
Company
Impact
Profile match
Headquartered in New York City, New York, Bloomberg is a global leader in financial technology, data, and business media. The company is best known for its proprietary Bloomberg Terminal, which provides financial professionals with real-time market analytics, trading tools, and execution capabilities. Through its multi-platform news division, it delivers economic reporting, research, and analysis across television, digital, print, and audio outlets worldwide.

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.

What’s the role?

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 experience is the full journey: the UI, the APIs, the semantic model, the provisioning flow, the feedback loops, the error states, the defaults, the automation, and the reliability of the systems underneath.

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.

This is not about adding a chatbot to a portal. It is about designing a new human-and-agent experience for Bloomberg’s data universe.

We’ll trust you to:

  • 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.
  • Bring product taste to engineering decisions, from interaction design and API shape to latency, observability, failure handling, and operational safety.
  • Help create new data experiences across portals, notebooks, query tools, programmable workflows, and agentic interfaces.
  • Design systems that are simple at the surface, but reliable, transparent, and scalable underneath.
  • Work with engineers across Bloomberg to understand how they use data and turn recurring friction into platform capabilities.
  • Mentor other engineers and contribute to the technical direction of the platform.

You’ll need to have:

  • 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.
  • Good design taste: clear workflows, useful defaults, fast feedback loops, understandable errors, safe automation, and interfaces that make complex systems feel simple.
  • A degree in Computer Science, Engineering, Mathematics, or equivalent practical experience.

We’d love to see:

  • 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.
  • Familiarity with technologies such as Kubernetes, Trino, Spark, notebooks, or lakehouse architectures.
  • 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.

Why this role is different

This role is about more than building infrastructure. It is about shaping how engineers experience data.

The hard part is not only scaling systems. It is designing the right abstractions, workflows, and interfaces so that powerful data infrastructure becomes simple, trustworthy, and useful. That requires engineering depth, but also imagination, taste, and execution.

You do not need to arrive as an expert in every technology we use. Prior experience with semantic technologies, data catalogs, or knowledge graphs is helpful, but not required. What matters most is your ability to learn deeply, think clearly, design thoughtfully, and build across the stack.

DataHub is where Bloomberg’s data becomes discoverable, understandable, usable, programmable, and operational.

This team builds that experience.

About Us

Meet the DataHub Engineering Team:

https://www.techatbloomberg.com/blog/meet-the-team-datahub-engineering/

If indicated, please note that years of experience are a guide; we will consider applications from all candidates who can demonstrate the skills necessary for the role.

Discover what makes Bloomberg unique - watch our podcast series for an inside look at our culture, values, and the people behind our success.

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