The Music Mission team owns Spotify’s end to end proposition for music creators and the experiences they create for fans. The team is dedicated to building tools and services to enable creation, promotion, expression, and monetization at scale.
The Music Mission enables creators to grow, engage, and monetize their fan bases on Spotify. At the heart of that mission is a suite of products including Discovery Mode, Marquee, Showcase, Music Videos, Clips, Listening Parties, and Concert Listings that help artists and their teams connect with listeners, grow audiences, and build sustainable careers.
We're looking for an Analytics Engineer to help shape how the Music Mission measures success. You'll build the data foundations, measurement frameworks, and analytics products that transform complex datasets into actionable insights. Working closely with engineers, data scientists, product managers, and business stakeholders, you'll help ensure teams can make confident, data-informed decisions that improve the experience for creators and fans around the world.
What You'll Do
- Build and maintain scalable data models and pipelines using dbt and BigQuery.
- Develop measurement frameworks, dashboards, and self-service analytics solutions that drive product decisions.
- Partner with Product, Engineering, and Data Science teams to define metrics and improve how we understand product performance.
- Translate business questions into reliable, well-modeled datasets and actionable insights.
- Improve data quality, observability, documentation, and governance across the Music Mission.
- Contribute to responsible AI practices, ensuring data and insights are trustworthy, transparent, and scalable.
- Participate in a support rotation for critical datasets and analytics products.
Who You Are
- You have experience in analytics engineering, data engineering, business intelligence, or a similar field.
- You have strong SQL skills and experience building data models with dbt.
- You have worked with cloud data platforms such as BigQuery, Snowflake, or Redshift.
- You are comfortable using Python and modern data orchestration tools to support analytics workflows.
- You understand instrumentation, data quality, and scalable measurement practices.
- You have experience building dashboards and enabling self-service analytics.
- You communicate clearly, collaborate effectively, and enjoy solving problems with cross-functional teams.
- You are curious about AI and emerging technologies and thoughtful about how they can be applied responsibly.
Where You'll Be
- This role is based in New York, NY.
- 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 $116,994 - $167,135 USD, 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, paid flexible holidays, and paid sick leave. These ranges may be modified in the future.
Skills Required
- Experience in analytics engineering, data engineering, or business intelligence
- Strong SQL skills
- Experience building data models with dbt
- Experience with cloud data platforms (BigQuery, Snowflake, or Redshift)
- Proficiency in Python to support analytics workflows
- Experience with modern data orchestration tools to support analytics workflows
- Understanding of instrumentation, data quality, and scalable measurement practices
- Experience building dashboards and enabling self-service analytics
- Collaborative communication with cross-functional teams
- Curiosity about AI and thoughtful application of emerging technologies
Spotify Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Spotify and has not been reviewed or approved by Spotify.
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Flexible Benefits — Employees consistently praise the total compensation package beyond base salary, highlighting a mix of RSUs, cash incentives, and stipends alongside core pay. The package is described as flexible and customizable through equity choices (e.g., RSUs, options, cash) that can be tailored for long-term wealth building.
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Leave & Time Off Breadth — Time-off offerings are repeatedly highlighted as substantial, including generous vacation, paid sick days, volunteer time, and flexible holidays. These policies are framed as a meaningful part of the overall rewards experience beyond salary.
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Healthcare Strength — Health coverage is portrayed as comprehensive, spanning medical, dental, vision, life insurance, disability coverage, and mental health support. Additional employer contributions to HSAs are cited as strengthening the overall health and wellness value proposition.
Spotify Insights
What We Do
Spotify transformed music listening forever when it launched in Sweden in 2008. Discover, manage and share over 50m tracks for free, or upgrade to Spotify Premium to access exclusive features including offline mode, improved sound quality, and an ad-free music listening experience.
