Data Engineer - Platform Central Data
Description
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, Python, and 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.