Data License Plus – Product Specialist - EMEA
AI in this role
As clients modernise their data architectures, move workloads to the cloud and explore AI and agentic workflows, their data needs are evolving rapidly. Bloomberg Data License Plus (DL+) brings together Bloomberg data, technology and delivery capabilities, providing trusted, governed and ready-to-use data for a broad range of enterprise use cases.
DL+ supports flexible consumption through bulk and security-level delivery, APIs, operational data stores, cloud-native and MCP delivery, enabling integration with modern data platforms, applications and research environments.
About the Role
As a Product Specialist for Data License Plus, you will be a technical pre-sales partner to Bloomberg’s EMEA Sales organisation, working directly with clients to understand their architecture, workflows and business objectives. You will translate client needs into compelling DL+ solutions, helping Sales identify opportunities, shape solutions and demonstrate Bloomberg capabilities. Sitting across Clients, Sales and Product, you’ll connect modern data technology with real business challenges and partner with Client Delivery to ensure a smooth transition into implementation.
What You'll Do
Technical Sales & Solution Design
- Partner with Sales on complex DL+ opportunities across EMEA.
- Lead technical discovery and translate client requirements into credible solutions.
- Deliver demonstrations, workshops and architecture discussions.
- Support evaluations and proofs of concept.
- Advise on APIs, bulk delivery, operational data stores and cloud-native distribution.
- Identify opportunities to modernise existing Bloomberg data workflows.
Sales Enablement & Market Development
- Build Sales confidence and capability in positioning DL+.
- Develop repeatable use cases, demonstrations and client stories.
- Support strategic campaigns and deliver training to client-facing teams.
- Share successful approaches and market learnings across the organisation.
Product Influence & Collaboration
- Provide Product teams with feedback on client needs and market trends.
- Identify opportunities for product enhancements.
- Translate the DL+ roadmap into clear client value propositions.
- Collaborate across Product, Engineering, Data, Sales and Client Delivery.
Pre-Sales Handoff
- Ensure requirements, scope and success criteria are clear before implementation.
- Partner with Client Delivery on structured handoffs for complex engagements.
You’ll Need to Have
- Experience in a client-facing technical pre-sales, product or solutions role within financial services, enterprise data or technology.
- Strong understanding of enterprise data architecture, APIs, cloud platforms and data integration.
- Hands-on experience with SQL, Python, APIs or similar technologies.
- Ability to translate technical requirements into solutions and business value.
- Strong presentation, demonstration and stakeholder-management skills.
- Commercial awareness and experience supporting complex enterprise sales.
We’d Love to See
- Experience with Bloomberg Data License, DL+ or comparable enterprise market data solutions.
- Knowledge of financial market data and enterprise workflows.
- Experience with Snowflake, Databricks, AWS, Azure or Google Cloud.
- Understanding of data governance and emerging AI and agentic workflows.
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. Discover what makes Bloomberg unique - watch our podcast series for an inside look at our culture, values, and the people behind our success.
How we rate this
Data License Plus – Product Specialist - EMEA at Bloomberg rates 69 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
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- List these exact terms on your resume: AI Agents and Databricks. An applicant tracking system matches the wording, not the idea.
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- Show where AI is part of your daily process, not a one-off project — this role expects it to be a running habit.
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