Senior Product Manager - Data Lakehouse (f/m/d)

Trusted Shops SE (DE); United States; Hybrid; USD 104,000 - 161,000; Full time

Job summary

Trusted Shops is seeking a Senior Product Manager for Data Lakehouse to own the product portfolio and roadmap, driving a shift from reactive requests to proactive, reusable metric standards. You will lead end-to-end data products, understand and serve internal stakeholders, and shape the semantic layer for BI and AI applications.

As part of a hybrid role, you will coordinate with cross-functional teams, align standards with finance data domains, and collaborate with data platform teams to

Responsibilities

• Own the product portfolio and roadmap for the Data Lakehouse domain, driving proactive, reusable metric standards.

Job description

Trusted Shops creates digital trust between people, businesses, and AI agents, with one clear goal: becoming the #1 Community of Trust. Every day, we help businesses build trust online and empower consumers to make confident decisions in an increasingly digital world.

As our products, reporting capabilities, and AI-driven use cases continue to grow, the company increasingly needs prepared, standardized data products – the data basis for self-service reporting, APIs (Metrics-as-a-Service), and AI-driven access via MCP or Chat interfaces. You and your team will own the whole journey from raw data to documented, trustworthy data products that people and machines can actually use.

To strengthen our Data Services department, we are looking for a

Senior Product Manager - Data Lakehouse (m/f/d)

(Hybrid in Cologne or remote in Berlin / Full-time / Permanent contract)

Responsibilities

• You own the product portfolio and roadmap for the domain, driving the shift from reactive requests ("build the metric asked for") to proactive, reusable metric standards.
• You run data products end-to-end. You know your consumers, treat them as customers, and track whether they actually trust and use what you ship.
• Together with your team, you define the semantic layer: metric and dimension definitions, metadata, and documentation that make a data product clear to people working in BI tools and reliable for AI agents.
• You provide metrics-as-a-service. Your team exposes metrics through an API that product engineering teams integrate directly into their own products.
• You are the point of contact for internal consumers and product teams: you set expectations, explain trade-offs, and say no when needed. You align shared standards and dimensions with the Finance Data Domain team and work with the Data Platform team as your service provider.