<div><span>We’re looking for an Analytics Engineer with a deep SQL/analytics toolkit to shape the analytics data layer that powers our Data Science environment. You’ll join a tight‑knit crew of analytics and data engineers, building robust, scalable models and pipelines in BigQuery and dbt across a huge and diverse data landscape. You’ll partner closely with Data Scientists, Data Engineers, and product teams to define clean data contracts, standardize metrics, and make trusted data easy to find and use.</span></div><div><br /></div><div><span>Join the band that turns billions of events into insight.</span></div><h3>What Youll Do</h3><ul><li>Be a primary contributor to the analytics data layer — designing, modeling, and maintaining datasets that surface critical signals from massive, heterogeneous sources.</li><li>Work hand‑in‑hand with Data Scientists to design schemas, features, and pipelines that unlock exploratory research and repeatable analysis.</li><li>Engineer novel datasets and features, and elevate existing ones, to enable flexible analysis of subscription and consumption dynamics across our platform.</li><li>Implement and evolve ETL/ELT pipelines in dbt and BigQuery; collaborate with the engineering team on data infrastructure improvements as needed.</li><li>Establish and champion reporting best practices and a standardized metrics layer for the Business Strategy &amp; Insights Org. — driving consistency, documentation, and discoverability.</li><li>Raise the bar on analytics engineering: code review, testing, data quality checks, performance optimization, observability, and CI/CD for analytics code.</li><li>Support downstream users — debugging queries, optimizing models, and sharing context — while mentoring teammates and uplifting standards.</li></ul><h3>Who You Are</h3><ul><li>2+ years of professional experience analyzing complex data with SQL and Python.</li><li>A demonstrable track record of contributing to analytics solutions for Data Science teams; you turn open-ended goals into scoped, actionable plans.</li><li>Significant ETL/ELT experience with very large and complex datasets, including managing DAG dependencies (e.g., Airflow, Dagster, or similar).</li><li>Deep competency with SQL on distributed/data-lake systems (e.g., BigQuery, Presto, Spark/Hive SQL), including nested data handling, window functions, query tuning, and partitioning strategies.</li><li>Collaborative, low-ego, and invested in helping peers level up. You care about reliable pipelines, clear models, and measurable impact.</li></ul><h3>Where Youll Be</h3><ul><li>This role can be based in New York City OR Stockholm</li><li>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. </li></ul><div>The United States base range for this position is $125,562 - 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. This range encompasses multiple levels. Leveling is determined during the interview process. Placement in a level depends on relevant work history and interview performance. These ranges may be modified in the future.</div><div><br /></div><div><span>Spotify is an equal opportunity employer. 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.</span></div><div><br /></div><div><span>At Spotify, we are passionate about inclusivity and making sure our entire recruitment process is accessible to everyone. We have ways to request reasonable accommodations during the interview process and help assist in what you need. If you need accommodations at any stage of the application or interview process, please let us know - we’re here to support you in any way we can.</span></div><div><br /></div><div><span>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.</span></div>

Spotify

Analytics Engineer - Business Strategy & Insights

Spotify

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