Company: Bloomberg L.P.
Location: London
Posted: April 4th, 2026
Location
London
Business Area
Data
Ref #
10050179
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 optimize the value of our data by combining domain and technical expertise to make data fit-for-purpose, timely, and accurate. We apply our problem-solving skills to identify innovative workflow efficiencies and deliver a high level of customer service.
As part of the Data Management and Operations (DMO) department, we're responsible for supporting the development, enablement and implementation of data management best practices that enable the delivery of “ready-to-use” data. As a Project Manager, you will be a technical leader across the organization, solving problems and devising solutions for data challenges.
You will orchestrate the work across the various teams of the group—from inception and modeling, through integration into the Semantic Platform and BQL, and beyond to engineering implementation in user-facing terminal applications. You are expected to navigate through unknowns and ambiguity while driving decisions and solutions that ensure technical alignment across the program of work. A key focus of this role is to modernize our workflows by helping to champion AI inclusion, moving the organization toward higher levels of automation, system efficiency, and improved process and collaboration speed.
*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.
Enable Technical Discussions: Facilitate high-level technical discussions to ensure alignment with system design, scalability, and best practices.
Champion AI & Automation: Identify and advocate for the inclusion of AI and Machine Learning within the data lifecycle to automate manual processes and increase overall system, process, and collaboration efficiency.
Ensure System Alignment & Deduplication: Audit existing data models and infrastructure to promote interoperability and prevent the redundant creation of pipelines where existing architectures should be utilized.
Orchestrate Technical Delivery: Coordinate the work of ontologists, platform integration engineers, data practitioners, and software engineers to ensure that commitments to users are realistic and met.
Design Interconnected Models: Develop interconnected data models and knowledge organization structures (taxonomies/ontologies) that elegantly conceptualize knowledge across multiple domains.
Manage Complex Programs: Lead the planning, execution, and delivery of complex, cross-functional programs, ensuring all milestones and deliverables are met on time and in-scope.
Bridge Product and Technical Leadership: Act as the primary link between product owners, technical leads, and individual contributors, keeping all parties aligned with the goal and removing obstacles to collaboration.
Stakeholder Management: Proven experience managing multiple stakeholders, deadlines, and competing priorities across a complex organization.
Technical Mastery: An appreciation of data management, including data modeling, metadata management, and the software development life cycle (SDLC).
System Design & Delivery: Demonstrated ability to translate business requirements into program objectives and work across teams to deliver on the design.
Communication: Excellence in communicating complex technical topics (including AI/ML concepts) with appropriate scope to varying audiences, from leadership to individual contributors.
AI/ML Inclusion: Experience identifying use cases for Large Language Models (LLMs) or Generative AI to enhance data discovery, classification, or metadata generation.
Technical Tooling: Experience with collaborative platforms such as MIRO and JIRA, and a passion for championing new collaborative tools (AI-assisted or otherwise) to improve team efficiency and transparency.
Semantic Technology Exposure: Knowledge of metadata systems, semantic technologies, linked data, and/or knowledge graphs.
Industry Standards: Understanding of Data Governance and Data Management, supported by industry certifications such as DAMA CDMP or DCAM.
FAIR Principles: Ability to enable the capture and storage of Bloomberg data in a manner that is findable, accessible, interoperable, and reusable.
Apply if you think we're a good match. We'll get in touch to let you know what the next steps are!
If indicated, please note that years of experience are a guide; we will consider applications from all candidates who can demonstrate the skills necessary for the role.
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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 amer_recruit@bloomberg.net
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