Senior Product Owner - Data & Analytics (m/f/d)

Yepoda

Contract type

Ongoing

Work mode

Hybrid · Hybrid (inferred: EU/NL where applicable)

Experience

Mid-level · 4+ years

Job description

Own the company-wide analytics function, including the KPI framework, reporting cadence, BI tooling/glossary, and decision-support and reporting standards
Own the product delivery roadmap for data initiatives for Yepoda's central Data analytics team
Translate commercial questions (CAC/LTV, channel mix, contribution margin, cohort behaviour, inventory turnover, etc.) from Marketing, Operations, Finance and other functions into scoped, prioritized data products and repeatable analyses
Write product requirements, user stories, and acceptance criteria that data engineering and analytics teams can execute against without ambiguity
Lead discovery and drive experimentation with stakeholders for new data capabilities, from self-serve analytics tooling to ML-powered features
Company mission
Information not specified

Core technologies

SQL

Dynamic start-up environment surrounded by a passionate and dedicated team
Accelerate your career with responsibility from day 1 and room for professional growth and advancement
Inspiring workspace in the heart of Berlin's Prenzlauer Berg, dog-friendly office, with free drinks and snacks
Hybrid working
Inclusive workplace that welcomes people from all different backgrounds, with flat hierarchies and trust by default
Employee discounts on Yepoda products to share with friends and family
Monthly benefits budget through the Probonio app to spend on what fits your lifestyle

3-5 years in a product management or product owner role in BI or Analytics or closely adjacent role at a relevant D2C, e-commerce, or consumer brand
Strong business understanding with a focus on impact, not just output
Deep understanding of D2C metrics (e.g., CAC, LTV, CIR/ROAS, contribution margin, cohort analytics, marketing attribution, etc)
Exceptional communication and stakeholder management skills, with proven ability to operate at C-level and translate fuzzy commercial questions into sharp, defensible analyses
Comfortable operating in ambiguity and moving fast in a startup environment; creates structure rather than waiting for it
Excellent written and spoken English
exposure to modern data stack concepts (data warehouses, self-serve analytics tools, ML pipelines)
experience writing SQL or working directly with data and AI tools such as Omni and Claude
SQL, Omni, Claude
SQL