Data Analytics Engineer, Experimentation

We are looking for an expert in engineering for analytics to join the band and help create an analysis-friendly data ecosystem across the growth team in Spotify.

In Product Insights, our mission is to turn terabytes of data into insights and get a deep understanding of how people use our apps to impact the product, strategy and direction of Spotify. In order to help us achieve this, the Analytics Engineer will build out an efficient analytics data suite so that we can create common data layers, build impactful visualizations and enable self-service insights for our data scientists.

You will work with data engineers, data scientists, user researchers and product managers to create a data architecture that ensures the right information is available and accessible to study user behavior, to build and track key metrics, to understand product performance and to fuel the analysis of experiments. Above all, your work will influence the future of Spotify and impact the way the world experiences music across the world.

What you’ll do:

  • Build lasting solutions to surface critical data and performance metrics.
  • Partnering with data scientists, you will design datasets and metrics to measure and optimize products.
  • You will build and be responsible for the analytics layer of our team’s data environment, making data standardized and easily accessible.
  • Work with the team to design, build and maintain a suite of visual dashboards.
  • Collaborate with, and mentor, data scientists in building efficient data pipelines and data sets.
  • Help drive optimization, testing and tooling to improve data quality.
  • Contribute to the development of the Product Insights function and the wider analytics community at Spotify.
  • Work from our offices in New York.

Who you are:

  • You have at least 4 years of experience in a similar business intelligence, data engineering, or data analysis role and a degree in science, computer science, statistics, economics, mathematics, or similar quantitative discipline.
  • Significant experience in designing analytical data layers and in conducting ETL with very large and complex data sets
  • Background in statistics or experience with controlled experiments
  • Knowledgeable in data modeling, data access and data storage techniques
  • High level of ability in SQL, Scala and Python
  • Understanding of standard methodologies to produce a high quality data environment that is easy to operate
  • You are capable of taking on loosely defined problems
  • You are a communicative person who values building strong relationships with colleagues and partners, enjoys mentoring and teaching others and you have the ability to explain complex topics in simple terms

We are proud to foster a workplace free from discrimination. We strongly believe that diversity of experience, perspectives, and background will lead to a better environment for our employees and a better product for our users and our creators. This is something we value deeply and we encourage everyone to come be a part of changing the way the world listens to music.

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