Data Scientist II – Performance Optimization Squad in London

Data Scientist II – Performance Optimization Squad in London

London Full-Time 60000 - 80000 € / year (est.) Home office (partial)
Spotify

At a Glance

  • Tasks: Build data foundations to optimise performance across Spotify's vast infrastructure.
  • Company: Join Spotify's innovative Performance Optimization Squad and make a real impact.
  • Benefits: Flexible work environment, competitive salary, and opportunities for personal growth.
  • Other info: Work in a diverse team that values inclusivity and innovation.
  • Why this job: Shape the future of data strategy while saving millions in costs.
  • Qualifications: Experience with cloud data, SQL, Python, and data visualisation tools.

The predicted salary is between 60000 - 80000 € per year.

The Performance Optimization Squad is a newly formed team in the Core Infrastructure Studio with a mission to establish a core competency in performance engineering and address systemic inefficiencies across Spotify's platform. With 3,200+ microservices, 40,000 VMs at peak, and 500,000 K8s pods, even minor fleet-wide efficiency improvements result in substantial cost savings. We've already identified $8M+ in annual savings from our first initiative alone, and we're just getting started. This squad works horizontally across the entire stack — but none of that optimization happens without the data to see it. We're looking for a Data Analyst who will build the measurement foundation that drives every decision we make.

What You'll Do

  • Optimization at this scale is only possible when someone can see the problem clearly. You'll build the data foundation from scratch; designing and owning the datasets, pipelines, and metrics that make performance inefficiencies visible across the platform.
  • Design, build, and maintain datasets and data pipelines that surface resource utilization, cost, and performance signals across Spotify's infrastructure.
  • Define and own metrics for efficiency, latency, and resource utilization; turning raw infrastructure signals into insights that drive prioritization.
  • Proactively investigate performance data to surface optimization opportunities, not just respond to engineering requests.
  • Build dashboards and analyses that support decision-making across the squad and partnering platform teams.
  • Work with engineers and platform teams to define guardrail metrics, validate findings, and measure the real-world impact of optimization efforts.
  • Translate complex infrastructure data into clear stories for both technical and non-technical audiences.
  • Own the data foundation: There is no inherited data infrastructure here; you'll design and build it from scratch. What gets measured, and how, is yours to define.
  • See your impact directly: Every insight you surface translates into cost savings. We measure success in dollars saved and efficiency gained; your work shows up in production.
  • Breadth at scale: Work across the entire Spotify platform; 3,200+ microservices, 40,000 VMs, 500,000 K8s pods. Few companies offer data problems at this scale.
  • Greenfield from day one: Help shape the culture, tooling, and data strategy of a brand new squad with strong executive support.

Who You Are

  • You have experience working with infrastructure, platform, or cloud cost data; Kubernetes metrics, cost attribution, utilization signals, or observability data feel familiar.
  • Or you're a strong technical analyst with enough grounding in distributed systems and cloud infrastructure to navigate GKE cost data, JVM metrics, and resource utilization signals.
  • You write clean, efficient SQL and Python; comfortable enough to model data and build lightweight pipelines, not just query existing tables.
  • You're self-directed: at your best when hunting for problems in the data, not waiting to be handed them.
  • Comfortable with ambiguity and able to carve your own path in an early-stage, unstructured environment.
  • Experienced with data visualization tools (Looker or similar) and know how to make a dashboard tell a story, not just display numbers.
  • You communicate clearly and confidently with engineers and non-technical stakeholders alike.

Where You'll Be

This role is based in Stockholm or London. 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.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Data Scientist II – Performance Optimization Squad in London employer: Spotify

Spotify is an exceptional employer that fosters a culture of innovation and inclusivity, making it an ideal place for Data Scientists looking to make a significant impact. With the opportunity to build data foundations from scratch in a newly formed squad, employees benefit from a flexible work environment in vibrant locations like Stockholm or London, alongside strong support for personal and professional growth. The company's commitment to diversity and accessibility ensures that every voice is valued, creating a dynamic workplace where meaningful contributions are recognised and rewarded.

Spotify

Contact Detail:

Spotify Recruiting Team

StudySmarter Expert Advice🤫

We think this is how you could land Data Scientist II – Performance Optimization Squad in London

Tip Number 1

Network like a pro! Reach out to current employees at Spotify or in the data science field. A friendly chat can give you insider info and maybe even a referral. We all know that sometimes it’s not just what you know, but who you know!

Tip Number 2

Prepare for those interviews! Brush up on your SQL and Python skills, and be ready to discuss how you've tackled data problems in the past. We want to see your thought process, so practice explaining your approach clearly and confidently.

Tip Number 3

Show off your projects! If you've built any dashboards or data pipelines, make sure to highlight them. We love seeing real-world applications of your skills, so bring your portfolio to the table and let your work speak for itself.

Tip Number 4

Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows us you’re genuinely interested in being part of the Spotify family. Let’s get you in the door!

We think you need these skills to ace Data Scientist II – Performance Optimization Squad in London

Data Analysis
SQL
Python
Data Pipeline Design
Kubernetes Metrics
Cost Attribution
Resource Utilization Signals

Some tips for your application 🫡

Tailor Your Application:Make sure to customise your CV and cover letter for the Data Scientist II role. Highlight your experience with performance engineering, data pipelines, and any relevant projects that showcase your skills in optimisation and data analysis.

Showcase Your Technical Skills:We want to see your SQL and Python prowess! Include examples of how you've used these languages to build datasets or analyse infrastructure data. If you've worked with Kubernetes metrics or cloud cost data, make that clear!

Communicate Clearly:Remember, you’ll be translating complex data into stories for both technical and non-technical audiences. Use your application to demonstrate your communication skills. A well-structured cover letter can go a long way!

Apply Through Our Website:Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role. We can’t wait to see what you bring to the table!

How to prepare for a job interview at Spotify

Know Your Data Inside Out

Before the interview, dive deep into the types of data you'll be working with. Familiarise yourself with Kubernetes metrics, cost attribution, and resource utilisation signals. Being able to discuss these topics confidently will show that you’re not just a candidate, but someone who understands the core of what the Performance Optimization Squad is all about.

Showcase Your Problem-Solving Skills

Prepare examples of how you've proactively identified performance inefficiencies in past roles. Think about specific instances where your insights led to significant cost savings or efficiency improvements. This will demonstrate your ability to hunt for problems in data rather than waiting for them to be handed to you.

Communicate Clearly with All Audiences

Practice translating complex technical data into clear, engaging stories. You’ll need to communicate effectively with both technical engineers and non-technical stakeholders. Consider preparing a few examples of how you've done this in the past, as it’s crucial for making your insights impactful across the squad.

Be Ready to Build from Scratch

Since this role involves designing and owning datasets and pipelines from the ground up, come prepared to discuss your approach to building data foundations. Share your thoughts on what metrics you would define and how you would ensure they drive decision-making. This shows initiative and aligns with the greenfield nature of the squad.