The Personalization team makes deciding what to play next easier and more enjoyable for every listener. From Discover Weekly to Wrapped, we’re behind some of Spotify’s most-loved features. We built them by understanding the world of music and podcasts better than anyone else. Join us and you’ll keep millions of users listening by making great recommendations to each and every one of them. We are looking for an analytics engineer to join our team of data scientists and business intelligence analysts. Our team describes user behavior through data so that product teams can track their progress, form hypotheses about what to improve, and evaluate changes that they have made. Having reliable, well-designed analytics datasets is crucial to this work. Join our Analytics Engineering group to help design and maintain these critical datasets! What You'll Do - Help build and maintain Personalization Mission’s analytics data stack, which includes designing tables, building/improving pipelines, unit testing, alerting and handling migrations and upstream data changes. - Work closely with data scientists and business intelligence analysts to understand the metrics, aggregations, and dimensions they need for their analyses. - Become an expert in Spotify’s first-party engagement data, based on usage behavior, so that you transform it into usable measurements. - Contribute to the development of the growing Analytics Engineering function and wider analytics and Data Science community at Spotify. - Spend your time thinking about how people listen to music and discover their next favorite song or band — and how to observe these behaviors in data. Who You Are - Deeply curious; interested in user behavior and excited to explore it proactively. - You have 3+ years of experience in a similar role developing and maintaining data pipelines and working with large scale data using SQL and Python. Knowledge of Google BigQuery is a plus. - Able to design foundational analytics tables that will serve a variety of uses. - Knowledge of dbt (or similar workflow and data warehousing tools). - Experience in conducting ETL with large and complicated datasets and handling DAG data dependencies. - Some experience with data visualization tools like Tableau or Looker Studio. - Capable of navigating ambiguity and solving loosely defined problems. - Experience using distributed data processing tools a plus (e.g. Spark). Where You'll Be - We offer you the flexibility to work where you work best! For this role, you can be within the EST time zone as long as we have a work location. Additional Information The United States base range for this position is $ 107,765 - $ 153,951, 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. These ranges may be modified in the future.
