Data Engineer - Financial Machine Learning

The AIR team helps Spotify make strategic decisions using machine learning and using our petabytes of data. From understanding and forecasting how podcasts are evolving on our platform, to modeling user behavior and how people like to consume music and podcasts. We work with teams across the company to model and quantify what happens on our platform, how that affects us and help them make better and data driven decisions through the use of ML and statistical inference.
Our team is seeking a motivated and self-driven data engineer to help us productionize our ML and data pipeline and apply best practices to manage, maintain and evolve complicated data streams over the lifecycle of various projects.

What you'll do

• Contribute to designing, building, evaluating, shipping, and refining data pipelines used for ML models and various other tools.
• Collaborate with a cross functional agile team spanning data engineering, data science, product management, and business stakeholders to build new data ingestion and transformation systems and help improve existing ones.
• Prototype new approaches and production-ize solutions at scale for our hundreds of millions of active users.
• Help drive optimization, testing, and tooling to improve quality of our data.
• Be part of an active group of data scientists and machine learning practitioners in New York and Stockholm.

Who you are

• You have a strong background in engineering, with experience and expertise in distributed systems and distributed computation.
• You have hands-on industry experience implementing production data pipelines at scale in Python, Scala, or similar languages. Experience with XGBoost, TensorFlow and machine learning frameworks is also a plus.
• You have experience with data pipeline tools such as Google Dataflow, Apache Beam/Scio, Spark, Flink or similar, and cloud platforms like GCP or AWS.
• You have experience working, building and deploying containerized services.
• You care about agile software processes, data-driven development, reliability, and disciplined experimentation.
• You love your customers even more than your code!

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.
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 with a community of more than 320 million users.