Description & Requirements
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.
Our Team
The Bloomberg Corporate Bonds Data team is responsible for the acquisition & publication of bonds being brought to market. Our responsibilities span across developing automated pipelines for ingestion & publication of data, enhancing the breadth & depth of our dataset, and developing a self describing data product to enhance discoverability. We are structured around solving client problems by closely partnering with Product, Sales & Engineering.
The Role
Within the Corporates Bonds' Data Modelling team, you would be responsible for leading the implementation of the data product vision for our corporate bonds discovery layer.
We'll trust you to:
* Audit and improve the existing fixed income data model to deliver a consistent, cross-platform client experience.
* Collaborate with Product, Engineering, Ontologists, and Fixed Income SMEs to co-design an interconnected data model supporting analysis across multiple datasets.
* Translate business and product requirements into clear, maintainable data modelling artifacts.
* Define and document metadata standards, entity relationships, and model schemas to support semantic alignment and discovery.
* Create tools and processes to monitor and maintain metadata inventories.
* Communicate data modelling requirements to stakeholders, and drive alignment across metadata/modelling functions to ensure practices are well understood & followed.
* Perform data profiling and root cause analysis to guide objective, data-driven modelling decisions.
* Promote FAIR data principles across the modelling lifecycle.
You'll need to have:
*Please note we use years of experience as a guide but we certainly will consider applications from all candidates who are able to demonstrate the skills necessary for the role.
* 4+ years of experience working with data modelling, metadata design, or semantic data structures*
* Proven ability to work with messy, heterogeneous data sources and convert them into harmonized, queryable formats
* Strong communication skills, with the ability to influence and drive alignment across technical and business stakeholders
* Experience working in cross-functional teams involving engineering, product, and subject matter experts
* Technical fluency, including comfort discussing modelling tradeoffs with engineers and reviewing data cataloging tools or APIs
* Demonstrated ability to think systemically about data interoperability, governance, and reusability
* Proficiency in Python and or SQL
We'd love to see:
* Exposure to fixed income or financial datasets (e.g. corporate bonds) - or a willingness to learn the domain
* Experience with data cataloging, metadata governance, or data discovery platforms
* Familiarity with semantic web or knowledge graph concepts (e.g., RDF, SKOS, OWL) and experience integrating these into usable data models. Formal ontology design is not required, but ability to collaborate with ontologists is essential
* Understanding of data governance frameworks or certifications (e.g., DAMA CDMP, DCAM)
* Exposure to the Bloomberg Terminal, Bloomberg API's or Enterprise Data products
* A degree (Bachelor's, Master's, or PhD) in a STEM discipline, Economics, Finance, or a related field
Does this sound like you?
Apply if you think we're a good match. We'll get in touch to let you know what the next steps are. #J-18808-Ljbffr