Data Scientist II – Performance Optimization Squad

Data Scientist II – Performance Optimization Squad

Full-Time 60000 - 80000 € / year (est.) No home office possible
Spotify

At a Glance

  • Tasks: Build data foundations to optimise performance across Spotify's vast infrastructure.
  • Company: Join Spotify, the world's leading audio streaming service, known for innovation and inclusivity.
  • Benefits: Flexible work options, competitive salary, and a culture that values diversity.
  • Other info: Shape the future of a new squad with strong executive support and growth opportunities.
  • Why this job: Make a real impact by driving efficiency and saving costs in a dynamic environment.
  • 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.

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 are the world’s most popular audio streaming subscription service.

Data Scientist II – Performance Optimization Squad 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 creativity thrives.

Spotify

Contact Detail:

Spotify Recruiting Team

StudySmarter Expert Advice🤫

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

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 how much that helps!

Tip Number 2

Show off your skills! Create a portfolio showcasing your data projects, especially those involving performance optimisation. Use real-world examples to demonstrate how your insights led to tangible results. We love seeing what you can do!

Tip Number 3

Prepare for the interview by brushing up on your SQL and Python skills. Be ready to discuss how you've tackled data challenges in the past. We want to see your problem-solving mindset in action!

Tip Number 4

Apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you're genuinely interested in joining our team. Let’s make this happen together!

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

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 optimisation, data pipelines, and any relevant projects that showcase your skills in building datasets from scratch.

Showcase Your Technical Skills:We want to see your technical prowess! Include examples of your SQL and Python work, especially if you've built lightweight data pipelines or visualised complex data. This is your chance to shine, so don’t hold back!

Communicate Clearly:Remember, you’ll be translating complex data into stories for both technical and non-technical audiences. Use clear language in your application to demonstrate your communication skills and how you can bridge the gap between data and decision-making.

Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen on joining our team at Spotify!

How to prepare for a job interview at Spotify

Know Your Data Inside Out

As a Data Scientist II, you'll be building datasets and pipelines from scratch. Make sure you understand the types of data Spotify uses, especially around infrastructure and performance metrics. Brush up on Kubernetes metrics and cost attribution to show you're ready to dive into the specifics.

Showcase Your Problem-Solving Skills

Prepare examples of how you've proactively identified and solved performance inefficiencies in past roles. Be ready to discuss your thought process and the impact of your solutions, as this role is all about turning raw data into actionable insights.

Communicate Clearly with Everyone

You'll need to translate complex data into stories for both technical and non-technical audiences. Practice explaining your past projects in simple terms, focusing on the outcomes and how they benefited the team or company. This will demonstrate your ability to bridge the gap between data and decision-making.

Be Ready for Ambiguity

This role is in a newly formed squad, so expect some uncertainty. Prepare to discuss how you've navigated unstructured environments before. Highlight your self-directed nature and how you carve your own path when faced with challenges, as this will resonate well with the team's culture.