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Principal Product Manager - Lounge Data Platform

in 10115, Berlin, Berlin, Deutschland
Unternehmen: DUDE CHEM
Vollzeit position
Verfasst am 2026-09-20
Berufliche Spezialisierung:
  • IT/Informationstechnik
    Dateningenieur, AI Künstliche Intelligenz, Daten Analyst, Wirtschaftsinformatik
Gehalts-/Lohnspanne oder Branchenbenchmark: 120000 - 180000 EUR pro Jahr EUR 120000.00 180000.00 YEAR
Stellenbeschreibung
Stellenbezeichnung: Principal Product Manager - Lounge Data Platform (all genders)

THE ROLE & THE TEAM

We are looking for a Principal Product Manager – Product Manager – Data Platform to lead the strategic roadmap, architecture, and deployment of our Lounge & Outlet data landscape. You play a pivotal role in driving business growth by unlocking the value of data in Zalando Lounge & Outlets.

The Data Platform team serves as the central foundation for Zalando Lounge & Outlets. We build the tools, infrastructure, and curated data products—spanning conversational analytics, tracking, semantic layers, reporting, and data governance that empower the organization to make data-informed decisions.

Partnering closely with the Head of Data Platform, you will bring a sharp product perspective to our technical strategy : driving product discovery, managing complex stakeholder needs, working closely with engineers and analysts, and establishing an AI-ready data foundation for intelligent agents, real-time decisioning, and machine learning.

Learn more about our culture and how our hiring process looks like.

INCLUSIVE BY DESIGN

At Zalando, our vision is to be the leading European technology platform for fashion and lifestyle – one that thrives on diversity and is truly inclusive by design. We believe that diverse teams fuel innovation and creativity, and we actively seek out talent from all backgrounds.

We actively seek to reduce bias in our hiring and employment processes, focusing on your qualifications, skills, and contributions. To support this, we kindly ask that you refrain from including personal details such as your photo, age, or marital status in your CV, ensuring a fair and equitable evaluation based solely on your abilities and potential.

We are committed to providing an exceptional and accessible candidate experience for everyone. If you require any accommodations to support you throughout the hiring process, please let us know – we are here to assist you.

Discover more about our commitment to creating a diverse and inclusive workplace:

WHAT WE'D LOVE YOU TO DO (AND LOVE DOING)

Turn strategy into outcomes:

  • Partner with the Head of Data Platform to shape and evolve the data-platform strategy using evidence from stakeholders, technology, and the wider market.
  • Translate business goals into a prioritized, transparent product roadmap and balance immediate business needs with long-term investments.
  • Communicate the roadmap and the reasoning behind priorities to technical and non-technical audiences.

Lead the data-product portfolio

  • Own the lifecycle of reusable data products across conversational analytics, tracking, reporting, and self-service.
  • Focus on building scalable platform capabilities rather than one-off fixes.
  • Define measures for adoption, usability, reliability, data quality, enablement and business impact.

Build an AI-ready data foundation

  • Define capabilities required for machine learning, predictive models, and AI agents—including feature stores, semantic layers, real-time data products, and metadata management.
  • Ensure data is designed for both human and machine consumption, with clear definitions, ownership, provenance, permissions, and quality expectations.
  • Drive literacy, governance, and adoption
  • Establish data ownership, improve product discoverability, empower self-service usage, and ensure responsible AI, privacy, and security standards.
WE'D LOVE TO MEET YOU IF
  • You have significant product-management experience, including ownership of complex data, platform, analytics, infrastructure, or enterprise products.
  • You have understanding of analytics platforms & reporting tools, event tracking, conversational analytics, experimentation, curated data products, semantic layers, feature stores, or reusable machine-learning features.
  • You have a good understanding of what makes a data…
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