Senior Data Management Professional - Data Product Owner - Entities
Tech Stack
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Agile @ 4
Communication @ 7
Compliance @ 3
Due Diligence @ 3
Prioritization @ 6
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
Bloomberg's Private Companies Data team is responsible for the company's private company data model, which supports research, investment analysis, compliance, and due diligence. The team links private company reference data with alternative data, ESG disclosures, financials, news, and other non-foundational datasets.
The Data Product Owner will lead the strategy, development, and integration of Bloomberg's Private Companies data model with non-foundational datasets. This role includes evaluating emerging datasets, identifying opportunities for differentiated products, and enabling advanced client workflows.
Responsibilities
- Own the end-to-end strategy and roadmap for Bloomberg's Private Companies data products, focusing on the integration of non-foundational datasets.
- Define the vision for a fit-for-purpose private company data model and align it with evolving client workflows in research, investment, and compliance.
- Research and validate use cases across private markets, including connections between company data and alternative data, ESG, financials, news, and emerging datasets.
- Lead discovery and prioritization activities to evaluate dataset structure, coverage, transparency, and delivery requirements.
- Translate client and stakeholder feedback into actionable requirements and define acceptance criteria for integrations and enhancements.
- Partner with Product, Engineering, and Data stakeholders to design data linkages and delivery models that maximize usability across products.
- Monitor data product health metrics, including completeness, coverage, linkages, and workflow adoption.
- Promote the importance of integrated private company data across Bloomberg and its client-facing workflows.
- Stay current on trends in private markets, data integration, and emerging non-traditional datasets.
Requirements
- 4+ years of experience working within financial or private markets data.
- Strong knowledge of private company research workflows and how private data is created, maintained, and consumed.
- Proven experience as a Product Owner or Product Manager for data platforms or large-scale datasets.
- Ability to define a product vision and communicate it clearly to technical and non-technical stakeholders.
- Experience developing product roadmaps, managing backlogs, and leading cross-functional delivery in Agile or hybrid environments.
- Data-driven mindset with comfort using metrics and KPIs to assess product performance and guide prioritization.
- Strong collaboration and communication skills, with experience working across Product, Engineering, and Data teams.
- Awareness of emerging private-market trends, including alternative data and ESG measurement.
- Familiarity with financial workflows that rely on integrated private company data, such as due diligence, investment analysis, and regulatory compliance.
- Understanding of third-party data providers and data integration strategies.
- Experience navigating ambiguity in complex, evolving markets.
Benefits
Benefits may include merit increases, incentive compensation for exempt roles, paid holidays, paid time off, medical, dental, vision, short- and long-term disability benefits, a 401(k) match, life insurance, and wellness programs.