At a Glance
- Tasks: Design and build scalable data pipelines for financial insights at Spotify.
- Company: Join Spotify, a leader in audio streaming, fostering creativity and innovation.
- Benefits: Flexible remote work, inclusive culture, and opportunities for personal growth.
- Other info: Collaborative environment with mentorship and career development opportunities.
- Why this job: Shape the future of financial data and drive strategic decisions.
- Qualifications: Experience with data processing frameworks and strong analytical skills.
The predicted salary is between 70000 - 90000 £ per year.
At Spotify, Financial Engineering is building the platform that powers Finance and enables strategic decision-making across the company. Our mission is to create trusted financial abstractions that make complexity manageable and insight actionable — supporting everything from premium and ads growth to forecasting, experimentation, and global reporting.
As engineers in the Financial Data Platform team, we turn messy, fragmented realities into clean, reusable foundations. We build core datasets that represent key financial domains like Premium, Ads, and Royalties. We create libraries and tools that empower others to produce and trust financial data at scale. We collaborate deeply with Finance, Product, and Data teams to unlock clarity and drive Spotify’s ambitions forward.
We are looking for engineers who are excited to shape the future of financial data at Spotify. You will design and operate scalable pipelines that process billions of records. You will apply product thinking to financial data — managing the full lifecycle from sourcing to documentation to exposure. You will define abstractions that simplify complexity and create intuitive paths for our consumers. Together, we advocate for standards, champion quality, and build systems that others can rely on with confidence.
If you thrive on building foundations that have broad, lasting impact, and want to work where financial data truly drives strategy, we’d love to work with you.
What You'll Do- Acquire a comprehensive understanding of how financial data supports diverse consumer needs, from Finance to broader business customers.
- Build core datasets and financial abstractions that serve as sources of truth for strategic and operational decision-making.
- Design, prototype, and build scalable data pipelines that process billions of data points reliably.
- Apply product thinking to data: manage the full data product lifecycle from sourcing to documentation and exposition, always prioritising consumer needs and success.
- Advocate for and implement effective data quality, engineering standards, and reusability.
- Collaborate closely with engineers, data scientists, finance collaborators, and business teams to build flexible, intuitive data products.
- Define data models and abstractions that simplify access to complex financial domains like Premium, Ads, and Royalties.
- Contribute to building tools and libraries that enable other teams to build financial data products at scale.
- Leverage mentorship and constructive feedback to foster accountability, growth, and collaboration within the team.
- Experienced with Data Processing Frameworks: Skilled with higher-level JVM-based frameworks such as Flink, Beam, Dataflow, or Spark.
- Comfortable with Ambiguity: Able to work through loosely defined problems and thrive in autonomous team environments.
- Skilled in Cloud-based Environments: Proficient with large-scale data processing in cloud environments, preferably with experience in Google Cloud Platform.
- Strong Analytical Skills: Adept at breaking down complex problems and communicating insights effectively.
- Knowledgeable About Data Modeling: You treat data as a product, with strong data modeling capabilities.
- Passionate About Clean Code: Committed to writing high-quality, maintainable code and building robust data pipelines.
- Curious and Inquisitive: You have a deep curiosity about data and systems, always seeking to understand and improve them.
- Skilled in large-scale data processing: Comfortable working with SQL and platforms like BigQuery.
- Excellent Collaborator: You value positive relationships across technical and business domains.
This role is based in London, United Kingdom. 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 revolutionising 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.
Remote Senior Data Engineer - Financial Data Platform in Poole employer: Spotify
At Spotify, we pride ourselves on fostering a dynamic and inclusive work culture that empowers our employees to thrive. As a Remote Senior Data Engineer in London, you'll enjoy the flexibility of working from home while collaborating with talented teams to shape the future of financial data. With a strong focus on mentorship, professional growth, and a commitment to quality, Spotify offers a unique opportunity to make a meaningful impact in a company that values creativity and innovation.
StudySmarter Expert Advice🤫
We think this is how you could land Remote Senior Data Engineer - Financial Data Platform in Poole
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Spotify!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Remote Senior Data Engineer - Financial Data Platform at Spotify.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Spotify.
✨Apply Directly through Our Website
When you find a suitable opening like Remote Senior Data Engineer - Financial Data Platform at Spotify, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Remote Senior Data Engineer - Financial Data Platform in Poole
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Spotify, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Spotify. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Spotify
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Spotify!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.