We’re looking for a mid-level Data Engineer to build data-driven engineering initiatives within Spotify’s Platform Mission on the Platform Central Data (PCD) squad, a mixed Data Engineering/Analytics Engineering team. You’ll design and operate reliable datasets and workflow automations that power developer productivity, platform health, leadership decision-making, and ML and AI Platform Metrics. Working shoulder to shoulder with our AE teammates, plus Product and Platform partners, you’ll turn complex platform signals into trusted, actionable data that helps Spotify ship faster and safer.

What You'll Do

Build and operate reliable, well-modeled data pipelines and products using SQL and Python or Scala, with strong testing, observability, and CI/CD. For distributed processing you will use Apache Spark or Scio, or equivalent technologies like Apache Beam or Flink.
Partner in a mixed DE and AE squad to translate complex platform and developer experience use cases into trustworthy datasets, metrics, and ML and AI insights workflows.
Improve data quality, performance, and cost efficiency across existing pipelines, including troubleshooting, backfills, and iterative hardening.
Collaborate with Product, Engineering, and Data Science partners to deliver end to end outcomes, from scoping and modeling to rollout and documentation.
Contribute to agile rituals and take part in a fair support rotation for key pipelines and datasets.

Who You Are

You have 3+ years building production quality data solutions with complex domain logic, and you use strong SQL to answer questions and debug problems.
You have experience with a cloud data warehouse, for example BigQuery, Snowflake, Redshift, or Databricks SQL, and with distributed processing frameworks such as Apache Spark or Scio (Scala for Apache Beam), or equivalents like Apache Beam or Flink.
You are comfortable with Python or Scala and with one or more transformation frameworks, for example dbt or equivalent SQL based transformations.
You have used a workflow orchestrator such as Airflow, Dagster, Prefect, or Flyte, and you care about reliability, monitoring, and testability.
You communicate clearly with both technical and non technical partners, and you can prioritize and deliver in a changing environment.
Experience in platform and developer productivity, experimentation, or ML and AI platform metrics is a plus.

Where You'll Be

This role is based in Toronto.
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.

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.

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.

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.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

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