Business Data Manager, Research

Position Description

We are looking for an exceptional self-starter to take ownership of the data management centre that lies at the heart of our research publishing and distribution platforms Every research report depends on accurate, structured and timely data covering analysts, companies, sectors, markets, research products, distribution rules and client entitlements. As guardian of this data, you will ensure its integrity while finding smarter ways to manage, automate and improve it. This is not a traditional admin role. You will have meaningful responsibility from the outset and work closely with research, publications, technology, compliance and operations. You will learn how a global equity research business turns intellectual content into a controlled, scalable digital product.

Key Areas of Responsibilities

1. Owning critical research data: Maintain reference data and metadata that underpins our publishing and distribution platforms, ensuring it is accurate, consistent and reliable.
2. Keeping publishing engine running: Monitor data integrity, investigate discrepancies and troubleshoot issues, understanding the root causes and impact across interconnected systems.
3. Improving and automating processes: Identify manual, repetitive or error-prone workflows and use data, scripting and automation to improve efficiency, controls, validation and exception reporting.
4. Connecting business and technology: Translate business requirements into clear data and system requirements and help colleagues understand the implications of changes across the platform.
5. Helping build what comes next: Contribute to initiatives that will shape the future.

Requirements

1. Degree holder or above in Computer Science, Engineering, Mathematics, Data Science, Economics, Finance or another quantitative or analytical discipline.
2. Minimum 3 years work experience in a corporate environment.
3. Strong analytical and problem-solving capabilities, with the intellectual curiosity to understand complex processes, data flows and interconnected systems.
4. Attention to details, with the ability to identify inconsistencies, investigate issues systematically and determine underlying root causes.
5. Comfortable working with large or complex datasets, with the ability to communicate clearly and effectively with both technical and non-technical stakeholders.
6. Capable to move confidently between detailed problem-solving and the bigger picture.
7. Take ownership, works methodically under pressure and is motivated to make things better.
8. Interest in financial markets, technology, or both.
9. Strong technical aptitude and willingness to learn new tools and technologies. Experience with SQL, Python, APIs, databases, Excel and/or data visualisation tools would be advantageous but is not essential.