Bloomberg runs on data, and in Data we're responsible for acquiring and providing it to our clients. We collect, model, analyze, and publish data which is the backbone of the Bloomberg Terminal. We apply problem-solving skills to identify innovative workflow efficiencies, and we implement solutions to enhance our systems, products and processes- all while delivering advanced insights to our clients.

The Team:

The Bloomberg Municipal Data team is responsible for acquiring, modeling, and publishing data across the U.S. public finance 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 Municipal Data team, you will lead the evolution of Bloomberg’s municipal data model and metadata framework. Your work will directly influence how clients discover, interpret, and analyze municipal securities.

We’ll trust you to:

• Represent the current state of alignment across municipal datasets, explain client use cases, and articulate why well-designed data models are essential to user workflows

• 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

• Experience working with heterogeneous or messy datasets and converting them into structured, queryable, harmonized 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

• Strong project management skills and ability to prioritize and adapt to tasks accordingly with a customer focused mentality

• Technical fluency, including comfort discussing modelling trade-offs, reviewing metadata tooling, and navigating APIs.

• Demonstrated ability to think systemically about data interoperability, governance, and reusability

• Practical experience using SQL or Python for Exploratory Data Analysis

We’d love to see:

• Familiarity with municipal bonds, public finance, or fixed income datasets

• Experience with metadata governance, data cataloging, or enterprise data discovery tools

• Knowledge of data governance frameworks such as DAMA CDMP or DCAM.

• Understanding of semantic web or knowledge-graph technologies such as RDF, SKOS, or OWL, and an ability to collaborate with ontologists

• Exposure to the Bloomberg Terminal, Bloomberg APIs, or Bloomberg Enterprise Data products.