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Product Manager – Data Platform

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Remote from
UK, Sweden
Salary
Undisclosed
Employment
Full Time
Experience
Senior
Published
Apply before
24 Nov 2026
Listing views
25
Application actions
2
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AI Summary

The role, at a glance.

Spotify is seeking a Product Manager to own strategy and delivery for its data catalogue, metadata, and data-lineage capabilities. The role serves a broad internal data community, including engineers, analysts, data scientists, ML practitioners, and AI agents. Responsibilities include roadmap development, problem prioritization, KPI definition, stakeholder alignment, and evaluating build, buy, or integration approaches. The Product Manager will partner closely with engineering, design, analytics, and data science teams to make data discovery, governance, and trust easier at scale. This is a technically oriented platform-product role with a hybrid work arrangement in London or Stockholm.

Role DNA

A quick view of the complexity, pace, ownership and collaboration implied by the job description.

Job Complexity

4/5
EasyHard

Pace & Pressure

4/5
RelaxedFast-paced

Autonomy Level

4/5
GuidedFull ownership

Communication Load

5/5
IndependentCollaborative
AI insightThe role requires product leadership across a complex, highly technical data-platform domain with many internal user groups and competing platform, business, and regulatory needs. Success depends on translating ambiguous data-governance and infrastructure problems into clear, measurable product decisions.

Salary analysis

Estimated compensation compared with the broader US market for similar roles.

Estimated job median (per year)Market rate
$135,000
US market range (per year)$110k–$165k
AI insightThe yearly pay period is inferred from the job context; it was not explicitly stated by the employer. No employer salary was disclosed. The figures are estimated annual USD compensation for a mid-level technical Product Manager focused on data-platform products; the yearly cadence is inferred from the full-time professional role and market convention.

Core skills

Skills and capabilities most closely associated with this opportunity.

Sample interview questions
How would you develop a product strategy for a data catalogue and lineage platform used by multiple internal teams?

I would begin by segmenting users and mapping their critical workflows, such as data discovery, access requests, impact analysis, and incident response. I would combine qualitative research with usage data to identify the largest trust and productivity gaps, then define a strategy around measurable outcomes such as discovery success, metadata coverage, lineage completeness, and time saved. The roadmap would sequence foundational platform capabilities before higher-level automation and AI-assisted experiences.

How do you prioritize requests from data engineers, analysts, data scientists, and compliance stakeholders when their needs conflict?

I make trade-offs transparent by evaluating each opportunity against user impact, strategic alignment, risk reduction, technical dependencies, effort, and expected adoption. I use a shared prioritization framework and communicate why an item is now, next, later, or not planned. For compliance or reliability risks, I ensure the decision accounts for the cost of inaction rather than only feature demand.

What metrics would you use to assess whether a data catalogue product is successful?

I would measure both platform health and user outcomes. Core metrics could include active users, search-to-success rate, percentage of critical datasets with complete ownership and metadata, lineage coverage, time to identify a trusted dataset, and reduction in duplicate or ungoverned datasets. I would also track qualitative confidence signals through recurring user feedback.

Describe how you would evaluate whether to build, buy, or integrate a third-party metadata-management solution.

I would define the target capabilities, user requirements, integration constraints, security and governance standards, total cost of ownership, and long-term extensibility. I would compare vendors and internal build options through a weighted evaluation, validate assumptions with a proof of concept, and assess how each option fits Spotify's existing data ecosystem. The recommendation would include delivery speed, operating costs, risks, and migration implications.

How would you work effectively with engineers on a highly technical platform product without becoming the technical decision-maker?

I would develop enough technical depth to understand architecture, constraints, dependencies, and trade-offs while relying on engineering partners for implementation ownership. My role is to provide clear problem framing, user evidence, desired outcomes, prioritization, and decision context. Regular discovery and planning sessions help ensure product and engineering decisions remain aligned throughout delivery.

This analysis is generated from the job description. Salary estimates, role characteristics and sample answers are guidance, not employer-provided facts.
Opportunity details

About this role.

Spotify’s mission is to unlock the potential of human creativity by giving a million creative artists the opportunity to live off their art and billions of fans the chance to enjoy and be passionate about these creators.

Data is a means to an end, and Spotify extracts value from data through application. The Data Platform Studio helps Spotify win by enabling the application of data in an intuitive and efficient way.

Data Platform is responsible for how data is collected, processed, stored, governed, and made available to the thousands of engineers, data scientists, analysts, and machine learning practitioners who build Spotify’s products. As AI agents increasingly generate code, write data pipelines, and power personalized user experiences, Data Platform sits at the center of one of the most important infrastructure domains at Spotify.

We’re looking for a passionate Product Manager to join the team responsible for Spotify’s data catalogue, metadata, and data lineage capabilities. In this role, you’ll own the strategy and roadmap for a critical part of Spotify’s data ecosystem, helping users discover, understand, trust, and safely use data at scale. You’ll work closely with engineers, designers, data scientists, and product teams across Spotify to make working with data faster, safer, and more intuitive.

What You’ll Do

  • Develop and own the product strategy and roadmap for Spotify’s data catalogue, metadata, and data lineage domain.
  • Diagnose and deeply understand the needs of Spotify’s data community, including data engineers, data scientists, analysts, ML engineers, and increasingly AI agents.
  • Identify and prioritize the highest-impact problems to solve, balancing user needs, business priorities, platform requirements, and regulatory considerations.
  • Evaluate and deliver solutions through building, buying, or integrating third-party products and capabilities.
  • Define success metrics and KPIs that measure adoption, value creation, and business impact.
  • Build strong relationships with internal product, engineering, analytics, and data teams to understand workflows, gather feedback, and shape future platform investments.
  • Collaborate closely with engineering, design, and data science partners to deliver high-quality platform experiences.
  • Influence stakeholders across the Data Platform Studio and broader Spotify organization to align around product direction and priorities.
  • Help shape how Spotify approaches metadata, governance, discoverability, lineage, and trust in an increasingly AI-driven world.
  • Stay informed on industry trends across data platforms, developer tools, AI/ML infrastructure, analytics, and data governance.

Who You Are

  • You have 2+ years of Product Management experience, ideally working on platform products, developer tools, data infrastructure, analytics platforms, or data governance systems.
  • You have a technical foundation through a degree in Computer Science, Engineering, a related field, and/or prior experience in engineering or technical roles.
  • You are comfortable working with engineers and can engage in technical discussions while representing customer and business needs.
  • You are an excellent communicator and collaborator who can build alignment across teams with different priorities and levels of technical expertise.
  • You have strong systems-thinking skills and can connect workflows, platforms, users, and business outcomes.
  • You have empathy for people who work with data and understand the challenges they face every day.
  • You enjoy working through ambiguity, breaking down complex problems, and creating clarity for teams.
  • You are curious about how AI is transforming the data landscape and are excited to help shape that future.
  • You lead with humility, build trust through collaboration, and help teams move forward with focus and momentum.

Where You’ll Be

  • This role is based in London or Stockholm
  • We offer you the flexibility to work where you work best! There will be some in person meetings, but still allows for flexibility to work from home.

Compensation

Additional Information

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