Data Product Manager – Analytics

Stellenbeschreibung:

Join Oldendorff Carriers as a Data Product Manager in Analytics and help make data‑driven decision‑making a genuine strength of Oldendorff. You will focus on one of our core business areas, such as Chartering, Finance, Fleet or Operations, acting as the primary link between that business and Data Engineering. The business defines the problem and the outcome it needs; you own how that outcome is achieved, from initial scoping through to real adoption in daily decision‑making.

Job Responsibilities

Act as the main analytical partner for stakeholders in areas such as Chartering, Finance, Fleet and Operations, translating business problems and desired outcomes into clearly scoped requirements and solution design, working iteratively with Data Engineering on feasibility and challenging technical constraints where they affect what gets delivered.
Own the roadmap across your portfolio of narrowly scoped data products and shape how work is sequenced based on business priorities.
Maintain the semantic layer for your data products, ensuring consistent business definitions, metrics and AI‑readable context, aligned with the organisation’s master data and single‑source‑of‑truth principles.
Enable self‑service access to your data product’s insights, primarily through AI‑driven tools such as conversational interfaces, natural‑language querying and proactive AI‑generated insights, so business users can get answers themselves. Where a dedicated interface is genuinely needed, prototype it yourself using AI tools to move fast and validate the concept; any prototype intended for production is handed over to Data Engineering for industrialisation once it passes defined maturity and governance criteria, while you retain ownership of the data product itself.
Use working proficiency in SQL and Python to explore data independently and validate outcomes against business logic.
Coordinate testing, rollout and ongoing refinement of your data products based on user feedback and evolving business needs, ensuring they are genuinely adopted and used for real decisions.

What success looks like

Management and stakeholders proactively bring you into their thinking early, not because a process requires it, but because your input makes their decisions better.
Your data products are actually used and trusted for real decisions, not just delivered and shelved.
Data Engineering can build confidently because what you have handed them is clear and well scoped.

What You Bring Along

Must‑have

At least 3 years of experience in an analytical, product or stakeholder‑facing role.
Strong ability to understand business problems and stakeholder needs, ask the right questions to clarify intent and translate ambiguous input into clear, actionable scope and solution design.
Ability to communicate complex analytical concepts clearly to both business stakeholders and technical teams, adapting your language and level of detail to the audience.
Working proficiency in SQL and Python, sufficient to explore data independently, build prototypes and hold your own in technical conversations with Data Engineering.
Confidence working with metrics, KPIs and semantic or business definitions.
Genuine interest in applying AI tools to analytical work and comfort adopting new tools as they emerge.
A proactive, hands‑on approach: comfortable prototyping and iterating with imperfect information and moving a topic forward rather than waiting for ideal conditions.
Excellent command of written and spoken English (the company’s working language).

Nice‑to‑have

Experience in or familiarity with shipping, commodity markets, macroeconomic analysis or finance.
Familiarity with Databricks, our core data platform.

What We Offer

Our corporate culture is special: relaxed and international, open and traditionally with flat hierarchies.
Since the very beginning, teamwork and quick decision making have been our success factors. Encouraging our employees to realize their ideas and initiatives is as important to us.