Product Manager - Third Party Data | Enterprise Data

We are Bloomberg Enterprise Data - fast paced, innovative, and growing. We partner closely with our clients to understand their businesses, data requirements, and financial technology needs. Our broad range of datasets, delivery channels, APIs, and cloud-enabled solutions enables clients to access the data they need, when they need it, and in the format that best supports their workflows.

Third-party data is a growth lever for Enterprise Data. Selectively sourcing and integrating external datasets enriches Bloomberg’s data products, closes coverage and quality gaps, and creates new client value. This role sits at the intersection of content strategy, data sourcing, and commercial partnerships.

We are seeking a Product Manager to grow Bloomberg’s Enterprise Data business through third-party data. You will identify priority datasets from external providers, evaluate their fit and commercial case, and lead their integration into Bloomberg data products to drive growth.

We’ll Trust You To

•Identify and prioritise third-party datasets that enrich Bloomberg’s data products and address client evolving needs.

•Build the business case for each dataset — client demand, commercial model, build-versus-buy, and integration cost.

•Evaluate providers on coverage, quality, licensing terms, and delivery, and lead commercial and partnership discussions alongside relevant teams.

•Define how third-party data is linked, normalised, and integrated with Bloomberg’s data estate.

•Partner with clients to validate demand and shape requirements.

•Work with Sales and Marketing to drive adoption and attain commercial outcomes.

•Manage specification, prioritisation, and backlog through an agile process across Data, Engineering, Legal, and Client Solutions.

You’ll Need to Have

•5+ years in product management or market experience within financial data, analytics, or investment technology.

•Experience delivering product outcomes through an agile process with cross-functional stakeholders.

•Excellent communication and negotiation skills.

•Understanding of how enterprise clients identify and evaluate datasets.

•Commercial judgement on dataset prioritisation, build-versus-buy, and content economics.

•Familiarity with data licensing, entitlements, and partnership structures.

•Working knowledge of AI, automation, and agentic approaches applied to data products.

•Ability to travel as needed.

We’d Love to See

•Experience in data acquisition, vendor management, or partnerships with data providers.

•Knowledge of the alternative data landscape and provider ecosystem.

•Proficiency with Python, SQL, or other data science tools.

•Experience with cloud-based data delivery, data marketplaces, or modern enterprise data platforms.