Backend Engineer II - Data Platform

Every dataset at Spotify, from the data behind creator royalties to the signals powering recommendations, is registered, published and traced through systems our team builds. We're the source of truth for what data exists at Spotify, where it lives, who owns it, and how it flows from one pipeline to the next.

These systems sit on the critical path of the platform. Data teams use them every day to publish and find data, and other platform teams build on them for access, retention, governance and incident response. That means our work is judged on correctness and reliability, because every system built on top of ours is only as good as the metadata we provide.

This is a backend role focused on data management, working on the problems at the core of any large data platform: running a data catalog that stays accurate at scale, capturing lineage across batch and streaming workloads, managing schemas as they evolve, and guaranteeing that consumers only read complete data. We build on open standards like OpenLineage and Apache Iceberg, and define the internal standards for naming, storage and metadata that the rest of Spotify builds against. As the platform takes on new storage technologies and new kinds of data assets, those standards and the systems behind them have to evolve with it, and you'll help decide how.

 

Build and Evolve Core Services: Design, build and operate the backend services and APIs behind our data catalog, lineage and publishing systems, and evolve them as the platform adopts new storage technologies and new kinds of data. Hold them to a high bar for correctness, performance and reliability.

Build Data Pipelines: Develop and run the batch and streaming pipelines that keep our metadata current, processing platform events and audit logs to capture how data is created and changed, and turning lineage and metadata into data products other teams build on.

Own Projects End to End: Turn what the teams using our platform need into technical designs, drive them through delivery and rollout, and own the results once they're in production.

Keep the Platform Healthy: Take part in on-call for critical services, build in observability and quality checks by default, and use automation, including AI tooling, to reduce toil for the team and our users.

You have solid experience building and running backend services and APIs in production with Java, and you care about API design, versioning and backward compatibility.

You're comfortable with SQL and have worked with data pipelines or a cloud data warehouse such as BigQuery, Snowflake or Databricks. Hands-on experience with batch or streaming frameworks like Beam, Flink or Spark is a plus.

You have a working understanding of data engineering concepts such as orchestration, metadata management, data quality, governance and lineage.

You break problems down into clear, shippable steps, reasoning through tradeoffs and risks and converging on clear recommendations.

You own the quality of what you ship, including code written with AI assistance, and you care about operating it well after launch.

You are a strong communicator and collaborator who enjoys working across teams, and you're comfortable in a dynamic platform environment where many engineers depend on what you build and priorities evolve with the business.