Team Leader – Credit Data Modelling

Team Leader – Credit Data Modelling Location

London

Data

Bloomberg runs on data. Our products are fueled by powerful information. We combine data and context to paint the whole picture for our clients, around the clock – from around the world. In Data, we are responsible for delivering this data, news and analytics through innovative technology - quickly and accurately.

We apply problem‑solving skills to identify innovative workflow efficiencies, and we implement technology solutions to enhance our systems, products and processes.

The Credit Data Modelling team sits at the core of our Fixed Income Data business, responsible for designing and maintaining the data models that underpin the discovery, integration, and analysis of credit‑related datasets. The team’s current focus is on corporate bonds within the wider credit space, with scope to expand into broader areas of the credit markets. The team partners closely with Product, Engineering, Ontologists, and Fixed Income subject matter experts to build scalable and interoperable data solutions that enable clients to navigate the complexity of credit markets with confidence.

We’re looking for a strong hands‑on people leader to manage and grow the Credit Data Modelling team. In this role, you’ll be responsible for leading a team of data modelling professionals who design, govern, and evolve the data structures supporting Bloomberg’s credit data products. You’ll coach and mentor team members, connecting day‑to‑day modelling tasks with our broader product strategy. You’ll also provide hands‑on guidance, lead technical discussions, and give direction and feedback to ICs in the team.

Finally, you’ll champion data governance, automation, and alignment with industry best practices to ensure the delivery of a robust and future‑proof data model.

• Lead and develop a high‑performing team of data modelling professionals, setting clear goals and fostering a culture of feedback, growth, and accountability.
• Translate product and business requirements into a coherent modelling vision that supports interoperability across datasets and delivery platforms, while proactively engaging stakeholders to promote best data modelling practices and demonstrate their benefits to our clients.
• Design and lead credit‑related data models and associated taxonomies, controlled vocabularies, and ontologies that conceptualize knowledge across multiple domains.
• Partner with Product, Engineering, and SMEs to co‑design data models that balance technical feasibility of legacy implementation with evolving client needs.
• Maintain and govern credit‑related data models and metadata: auditing and evolving models and fields, and defining/enforcing metadata standards, entity relationships, and schemas to ensure consistency, accuracy, discoverability, and client value.
• Drive governance practices: communicate data governance requirements to stakeholders, embed robust governance processes, ensure adherence to FAIR principles, and align with Bloomberg’s modelling standards.
• Promote the practice of data modelling/ontology design and metadata management as part of the full data lifecycle across the wider Credit group, including driving workflow automation and tooling to increase scalability and resilience.
• Communicate progress, priorities, and technical concepts clearly across both technical and non‑technical stakeholders.
• Influence decision makers across the firm to adopt certain perspectives and align to shared standards that improve client outcomes.

• 3+ years of experience leading and developing high‑performing teams, ideally within data management, modelling, or related fields.
• Strong background in data modelling, metadata design, or semantic data structures.
• Proven ability to work with complex, heterogeneous datasets and convert them into harmonized, queryable formats — for example, unifying disparate datasets into a single schema, normalizing multiple vendor feeds into a harmonized model, or developing pipelines that reconcile internal and external sources into queryable formats for analytics.
• Strong…