Data Engineer Revenue Platform

Promote Project
City of London
3 weeks ago
Create job alert

At Spotify, we're building the revenue platform that drives how revenue and taxes are processed across the company — enabling reliable, scalable financial operations across every market, product line, and partner. Our systems are essential to Spotify’s ability to earn, track, and report revenue and taxes, supporting everything from subscriptions and advertising to creator payouts.


As engineers on this team, we design and maintain the backend and data platform capabilities that power millions of transactions each day with precision. We build services that handle tax calculations, produce compliant financial records, and support regulatory requirements across global markets — all while staying agile to keep up with Spotify’s evolving business models. We equip Finance teams with flexible, configurable tools that govern how revenue and taxes are applied across products, enabling rapid adjustments without needing deep technical expertise. Our modular, process-oriented components simplify the development, maintenance, and scaling of the critical Order to Cash enterprise process that underpin Spotify’s financial operations.


Data Engineer, Revenue Platform
Location

London


What You'll Do

  • Gain deep expertise in Spotify’s revenue platform, understanding how it enables financial operations, compliance, and strategic decision‑making.
  • Design and implement scalable backend and data systems that process millions of transactions daily — supporting accurate tax calculation, billing, revenue recognition, financial configuration, and tax reporting.
  • Build intuitive, self‑serve tools that empower Finance teams to define and manage product‑specific revenue and tax configuration independently, without requiring engineering involvement.
  • Develop and enhance modular platform capabilities that encode critical enterprise workflows, promoting consistency, reusability, and ease of maintenance across financial systems.
  • Lead the creation of new platform capabilities within the Tax Solutions space, focusing on Tax Reporting and global regulatory compliance.
  • Partner closely with Engineers, Product and Finance stakeholders to design systems that are scalable, auditable, and highly reliable.
  • Champion engineering best practices, strong architectural design, and operational excellence across backend and data platforms.
  • Foster a collaborative team culture rooted in shared ownership, constructive feedback, and continuous improvement.

Who You Are

  • You have experience in data engineering, including building and maintaining data pipelines.
  • You are proficient in Python and ideally Scala or Java.
  • You possess a foundational understanding of system design, data structures, and algorithms, coupled with a strong desire to learn quickly, embrace feedback, and continuously improve your technical skills.
  • You’re familiar with cloud‑native development and deployment, ideally within the Google Cloud Platform.
  • You think critically about system design and strive to build solutions that are reliable, maintainable, and auditable at scale.
  • You have good communication skills and can articulate your ideas and ask clarifying questions.
  • You love collaborating with others.
  • You thrive in ambiguous and fast‑changing environments, and know how to make progress even when requirements are evolving.
  • You approach platform engineering with empathy for your users — prioritising usability, configurability, and long‑term sustainability.
  • You care deeply about code quality, testing, and documentation, and you aim to build systems that are easy to understand and operate.
  • You enjoy collaborating across functions and bring clarity and alignment when working with engineering, finance, and product partners.
  • You’re naturally curious, self‑motivated, and always looking for ways to grow your technical skills and improve how things are done.

Where You'll Be

  • 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 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.


Job type

Remote job


Tags

  • design
  • system
  • python
  • music
  • technical
  • support
  • code
  • financial
  • finance
  • cloud
  • scala
  • operations
  • operational
  • engineer
  • engineering
  • recruitment
  • backend
  • digital nomad


#J-18808-Ljbffr

Related Jobs

View all jobs

Data Engineer, Revenue Platform — Remote & Global

Senior Data Engineer IND (Remote)

Data Engineer

Data Engineer

Senior Data Engineer

Senior Data Engineer

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.

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.