Data Engineer - Subscriptions

We in the Machine Learning product area in the Activation, Retention, Conversion studio are focused on building robust and scalable machine learning solutions that can personalize activation, retention and conversion funnels to improve important business metrics. Through an ensemble of machine learning models, we aim to provide the best suitable offer or non-credit card trial to demonstrate the value of Spotify Premium, with the ultimate goal of having direct impact on key business metrics like SUBs and MAU.

Our vision is to build the machine learning models and infrastructure that offers a fully personalized and ML-optimized Offer as well as trial targeting with the intention of showing the right value to the right user at the right time.

Our key problem areas are:

1. When is the best time to give Offers to users for optimal profitability?
2. What is the right offer to give a user to maximize the probability of them converting?
3. What is the right amount of friction to introduce using feature capping?
4. For new users signing up on the platform which non-credit card trial to give?

Our squad is a combination of Machine Learning Engineers, Backend Engineers and Data Scientists. If this sounds like something you would be interested in working on, please apply.

• Design and build large-scale batch and real-time data pipelines with data processing frameworks like Scio, Dataflow and BigQuery.
• Design, build and maintain scalable backend services. Help drive optimization, testing and tooling to improve data quality.
• Mentor and coach other engineers on data engineering best practices.
• Create, update and evangelize standards and documentation that improve the experience for people working with data at Spotify.
• Collaborate with other data, backend and ML engineers, data scientists, managers and stakeholders.
• Be a valued member of a multi-functional agile team which continuously experiments, iterates, and delivers on new product objectives.

• You have a strong understanding of data systems.
• You have a strong understanding of distributed systems.
• You are knowledgeable and passionate about improving and building data platforms.
• You have experience with Backend / Data engineering.
• You are familiar with Machine Learning and would be interested in collaborating with Machine Learning Engineers to deliver Machine Learning models into production.
• You are familiar with current engineering practices such as distributed architecture.
• You have experience with one or more higher-level JVM-based data processing frameworks such as Beam, Dataflow, Crunch, Scalding, Storm, Spark.
• You will have experience working with Scala and Java. Python, Scio & Luigi would be an encouraged bonus.
• You are curious about new technologies and finding uses and insights for all types of data.
• You have the desire and ability to contribute across different disciplines.

• This role is based in New York.
• 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.

The United States base range for this position is $143,499 - $179,374 plus equity. The benefits available for this position include health insurance, six-month paid parental leave, 401(k) retirement plan, monthly meal allowance, 23 paid days off, 13 paid flexible holidays, paid sick leave. These ranges may be modified in the future.