Senior Financial Data Quality Specialist
We're Bloomberg Enterprise Data - fast paced, innovative and expanding. We have worked hard and smart to become the $1bn business we are today. We partner closely with our clients, taking time to understand their unique businesses and individual data and technology needs. Our endless selection of datasets, covering all asset types, with multiple delivery technologies and flexible scheduling mean our clients are able to get exactly the data they need, when they need it, in the format they prefer. Without us, they simply can't operate.
In this role you, will be working with the Bloomberg Enterprise Data - Data Quality team. We perform an essential function at Bloomberg, by making sure that Bloomberg has the highest quality, fit for purpose, financial data in the world. This role requires a passion for financial data and financial instruments. Our approach to data quality involves writing accurate definitions for securities in different asset classes, and applying those definitions across massive amounts of data on a daily basis. We are constantly writing new definitions, revising definitions, and working with our Global Data teams to correct any inaccurate data. We check data both for correct values and for machine readability.
Ideally, you are familiar with Linked Data, RDF data, SHACL, and SPARQL. You have experience using technology to help you solve problems and create working prototypes, such as jupyter notebooks. You are familiar with ISO 20022. You have your own worldview of financial instruments across asset classes and are comfortable writing exact definitions in a constraint language like SHACL, which can be applied to data. We'll trust you to:
You should have:
- Operate in an influential business role
- Write financial definitions that can be used for data quality
- Apply data quality definitions to vast amounts of data
- Work in jupyter notebooks (python) and test new data quality rules
- Analyze data quality test results
- Grow your business and technology skills
- Evaluate what is possible and viable
- Work with Engineering and other global teams
If this sounds like you:
- Extensive experience with financial data
- Familiar with using large structured data models and datasets to solve problems
- Experience with and/or a desire to work with: Linked Data, Semantic Web, RDF, RDFS, OWL, SHACL, RDFa, Graph Data, Knowledge Graph, and Knowledge representation and reasoning
- Experience with tools to handle large diverse data sets
- Knowledge of large structured data models
- The ability to address multiple priorities in an extremely fast-paced environment
Apply if you think we're a good match! We'll get in touch to let you know what the next steps are, but in the meantime feel free to have a look at this:
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.