At a Glance
- Tasks: Lead data modelling for corporate bonds, enhancing client experience and collaborating with cross-functional teams.
- Company: Bloomberg delivers powerful data and analytics, shaping the financial landscape globally.
- Benefits: Enjoy a diverse workplace, opportunities for growth, and a commitment to inclusivity.
- Why this job: Join a dynamic team driving innovation in data management and make a real impact.
- Qualifications: 4+ years in data modelling, strong communication skills, and proficiency in Python or SQL required.
- Other info: Open to all candidates who can demonstrate necessary skills, regardless of formal experience.
The predicted salary is between 43200 - 72000 £ per year.
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:
- 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.
- Understanding of data governance frameworks or certifications (e.g., DAMA CDMP, DCAM).
- Exposure to the Bloomberg Terminal, Bloomberg APIs 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. Bloomberg is an equal opportunity employer and we value diversity at our company. We do not discriminate on the basis of age, ancestry, color, gender identity or expression, genetic predisposition or carrier status, marital status, national or ethnic origin, race, religion or belief, sex, sexual orientation, sexual and other reproductive health decisions, parental or caring status, physical or mental disability, pregnancy or parental leave, protected veteran status, status as a victim of domestic violence, or any other classification protected by applicable law. Bloomberg is a disability inclusive employer. Please let us know if you require any reasonable adjustments to be made for the recruitment process. If you would prefer to discuss this confidentially, please email.
Senior Data Management Professional - Data Modeling - Corporate Bonds London, GBR Posted today employer: Bloomberg L.P.
Contact Detail:
Bloomberg L.P. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Management Professional - Data Modeling - Corporate Bonds London, GBR Posted today
✨Tip Number 1
Familiarise yourself with Bloomberg's products and services, especially those related to corporate bonds. Understanding their data models and how they integrate with other financial datasets will give you a significant edge during interviews.
✨Tip Number 2
Network with professionals in the data management and financial sectors. Attend industry events or webinars where you can meet people who work at Bloomberg or similar companies. This can provide insights into the company culture and expectations.
✨Tip Number 3
Brush up on your technical skills, particularly in Python and SQL. Consider working on personal projects that involve data modelling or metadata design to showcase your abilities and problem-solving skills relevant to the role.
✨Tip Number 4
Prepare to discuss your experience with cross-functional teams and how you've influenced stakeholders in previous roles. Be ready to share specific examples of how you've tackled complex data challenges, as this will demonstrate your fit for the collaborative nature of the position.
We think you need these skills to ace Senior Data Management Professional - Data Modeling - Corporate Bonds London, GBR Posted today
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data modelling, metadata design, and any specific tools or technologies mentioned in the job description. Use keywords from the job listing to ensure your application stands out.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Discuss how your background aligns with the responsibilities of the position, particularly your experience with cross-functional teams and data governance.
Showcase Technical Skills: Clearly outline your proficiency in Python and SQL, as well as any experience with data cataloging or semantic web concepts. Providing examples of past projects where you applied these skills can strengthen your application.
Highlight Collaborative Experience: Since the role involves working closely with various stakeholders, emphasise your ability to communicate effectively and drive alignment across technical and business teams. Include specific instances where you successfully collaborated on projects.
How to prepare for a job interview at Bloomberg L.P.
✨Understand the Data Landscape
Familiarise yourself with the types of data Bloomberg handles, especially in corporate bonds. Be prepared to discuss how you would approach data modelling and the challenges associated with messy, heterogeneous data sources.
✨Showcase Your Technical Skills
Highlight your proficiency in Python and SQL during the interview. Be ready to discuss specific projects where you've used these skills to solve data-related problems, particularly in relation to data modelling and metadata design.
✨Communicate Effectively
Demonstrate your strong communication skills by clearly articulating your ideas and experiences. Practice explaining complex data concepts in simple terms, as you'll need to influence and align with both technical and business stakeholders.
✨Emphasise Collaboration Experience
Prepare examples of your experience working in cross-functional teams. Discuss how you've collaborated with engineers, product managers, and subject matter experts to achieve common goals, particularly in data modelling or governance.