Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Data Engineering Manager - Platform and Partner Experience

Spotify
City of London
4 days ago
Create job alert
Data Engineering Manager - Platform and Partner Experience

Delivering the best Spotify experience possible. To as many people as possible, in as many moments as possible. That’s what the Experience team is all about. We use our deep understanding of consumer expectations to enrich the lives of millions of our users all over the world, bringing the music and audio they love to the devices, apps and platforms they use every day.


We are seeking a motivated and experienced Data Engineering Manager to lead a team within our Partner and Platform Experience studio. This team is at the heart of how we power insights and product experiences from data across some of Spotify’s most widely used devices, features and technology partnerships. If you’re excited by team leadership and owning and developing data systems that help us understand user experience — whilst being close to cutting‑edge digital product development — this is the role for you.


What You’ll Do

  • Lead and coach a team of Data Engineers working on high‑impact products and data infrastructure
  • Set and deliver the team’s roadmap in close collaboration with Data Science Managers, Product Managers, and other Engineering Managers
  • Identify & deliver (via your team) new opportunities for data engineering to support product improvements & features
  • Maintain and evolve our existing data pipelines and internal data products
  • Foster a collaborative, inclusive, and high‑trust engineering culture
  • Influence and support the development of the technical architecture of the team’s stack, including identifying opportunities to use emerging technologies (e.g., AI) to improve processes and drive efficiencies
  • Champion data quality and best practices across the Studio

Who You Are

  • An experienced data engineering manager and people leader
  • Confident managing stakeholders across multiple levels, and a strong collaborator with data science teams
  • Excellent at influencing without authority and being an effective communicator (both written and verbal)
  • Passionate about growing both people and systems, building teams and technical foundations that scale
  • Empathetic towards stakeholder needs and comfortable translating these into technical requirements
  • Ideally proficient in some or all of the following technologies: SQL/dbt, Scala, Java, Python and Google Cloud Platform
  • Have a background in Computer Science with specific Data Engineering experience. Some product management experience would be a bonus.

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.

Spotify is an equal opportunity employer. You are welcome at Spotify for who you are, no matter where you come from, what you look like or what’s playing in your headphones. Our platform is for everyone, and so is our workplace. The more voices we have represented and amplified in our business, the more we will all thrive, contribute, and be forward‑thinking! So bring us your personal experience, your perspectives, and your background. It’s in our differences that we will find the power to keep revolutionizing the way the world listens.


At Spotify, we are passionate about inclusivity and making sure our entire recruitment process is accessible to everyone. We have ways to request reasonable accommodations during the interview process and help assist in what you need. If you need accommodations at any stage of the application or interview process, please let us know – we’re here to support you in any way we can.


Spotify transformed music listening forever when we launched in 2008. Our 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. Everything we do is driven by our love for music and podcasting. Today, we’re the world’s most popular audio streaming subscription service.


#J-18808-Ljbffr

Related Jobs

View all jobs

Data Engineering Manager

Data Engineering Manager

Data Engineering Manager

Data Engineering Manager

Data Engineering Manager

Data Engineering Manager

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Data Science Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.

Data Science Team Structures Explained: Who Does What in a Modern Data Science Department

Data science is one of the most in-demand, dynamic, and multidisciplinary areas in the UK tech and business landscape. Organisations from finance, retail, health, government, and beyond are using data to drive decisions, automate processes, personalise services, predict trends, detect fraud, and more. To do that well, companies don’t just need good data scientists; they need teams with clearly defined roles, responsibilities, workflows, collaboration, and governance. If you're aiming for a role in data science or recruiting for one, understanding the structure of a data science department—and who does what—can make all the difference. This article breaks down the key roles, how they interact across the lifecycle of a data science project, what skills and qualifications are typical in the UK, expected salary ranges, challenges, trends, and how to build or grow an effective team.