Time since we first saw it
Day 35
Similar jobs usually come down between day 6 and day 54.
At Spotify, jobs usually come down by about day 39.
From 11,453 similar postings that came down, and 43 of Spotify’s. Coming down is not always a hire.
Stockholm
Live, first seen by us 35 days agoEmployment type Permanent
Employment type in the employer’s posting: PermanentFrom the employer’s posting
Design, build and operate backend services and APIs for the data catalog and lineage
Develop batch and streaming pipelines that keep metadata current from platform events and audit logs
Turn team needs into technical designs and drive them through delivery and rollout
Take part in on-call for critical services and build in observability and quality checks
Design, build and operate the backend services and APIs behind our data catalog, lineage and publishing systems
Develop and run the batch and streaming pipelines that keep our metadata current, processing platform events and audit logs
Turn what the teams using our platform need into technical designs, drive them through delivery and rollout
Take part in on-call for critical services, build in observability and quality checks by default
solid experience building and running backend services and APIs in production with Java
You're comfortable with SQL
have worked with data pipelines or a cloud data warehouse such as BigQuery, Snowflake or Databricks
You have a working understanding of data engineering concepts such as orchestration, metadata management, data quality, governance and lineage.
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.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 35
Similar jobs usually come down between day 6 and day 54.
At Spotify, jobs usually come down by about day 39.
From 11,453 similar postings that came down, and 43 of Spotify’s. Coming down is not always a hire.
16 open jobs
Open jobs by the week we first saw them, last 12 weeks.
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Who You Are - 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 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.
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. What You'll Do
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Yes. We’ve followed one other Backend Engineer - Data Platform job there since October 2026. It is still up.
New Data Engineer postings at the employers we follow are up 8% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
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.
Permanent
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Stockholm
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