Senior Data Engineer - Data Platform
London
- Pay
- Salary not listed in the saved posting
- Work setup
- Unconfirmed
- Employment
Permanent — employment source
Employment type Permanent
Read the full posting
What you’ll work on
Full postingCollaborate with product and engineering teams to build and support critical data infrastructure and datasets.
Build systems that collect and process user behaviour data at scale.
Design and evolve data architectures that support high data volumes and a broad range of internal users.
From the employer’s posting
What You'll Do Collaborate with product and engineering teams to build and support critical data infrastructure and datasets. Build systems that collect and process user behaviour data at scale.
Collaborate with product and engineering teams to build and support critical data infrastructure and datasets. Build systems that collect and process user behaviour data at scale. Help power Spotify’s personalization and recommendation systems, as well as the tools teams use to build and test new features.
Help power Spotify’s personalization and recommendation systems, as well as the tools teams use to build and test new features. Design and evolve data architectures that support high data volumes and a broad range of internal users. Improve the reliability, scalability, and usability of our data infrastructure.
What you’ll bring
All qualificationsCore experience
- You have experience with JVM-based data processing frameworks such as Flink, Beam, Dataflow, or Spark.
- You have experience with data modeling and schema design.
Qualification wording
You have experience with JVM-based data processing frameworks such as Flink, Beam, Dataflow, or Spark.
You have experience with data modeling and schema design.
Tools in this posting
- SQL
- Kubernetes
- Java
- Spark
- BigQuery
Source — Tool mentions in context
- You are an experienced Data Engineer, and proficient in backend development using Java. - You are comfortable working with large-scale datasets using SQL and platforms such as BigQuery. - You have experience with JVM-based data processing frameworks such as Flink, Beam, Dataflow, or Spark.
- You have experience with JVM-based data processing frameworks such as Flink, Beam, Dataflow, or Spark. - You are familiar with DevOps practices, cloud infrastructure, containerized applications, and Kubernetes fundamentals. - You have experience with data modeling and schema design.
Who You Are - You are an experienced Data Engineer, and proficient in backend development using Java. - You are comfortable working with large-scale datasets using SQL and platforms such as BigQuery.
- You are comfortable working with large-scale datasets using SQL and platforms such as BigQuery. - You have experience with JVM-based data processing frameworks such as Flink, Beam, Dataflow, or Spark. - You are familiar with DevOps practices, cloud infrastructure, containerized applications, and Kubernetes fundamentals.
Job description
The Platform team creates the technology that enables Spotify to learn quickly and scale easily, enabling rapid growth in our users and our business around the globe. Spanning many disciplines, we work to make the business work; creating the infrastructure, tooling, frameworks, and capabilities needed to welcome a billion customers.
The Data Platform team develops and maintains the infrastructure that supports Spotify’s data ecosystem. Within Data Platform, the Data Collection product area builds infrastructure that makes it easier to collect and consume data at scale. You’ll join a team focused on making user behaviour data seamless and reliable for data teams across Spotify.
What You'll Do
- Collaborate with product and engineering teams to build and support critical data infrastructure and datasets.
- Build systems that collect and process user behaviour data at scale.
- Help power Spotify’s personalization and recommendation systems, as well as the tools teams use to build and test new features.
- Design and evolve data architectures that support high data volumes and a broad range of internal users.
- Improve the reliability, scalability, and usability of our data infrastructure.
- Work across disciplines to solve complex data challenges and make an impact across Spotify.
Who You Are
- You are an experienced Data Engineer, and proficient in backend development using Java.
- You are comfortable working with large-scale datasets using SQL and platforms such as BigQuery.
- You have experience with JVM-based data processing frameworks such as Flink, Beam, Dataflow, or Spark.
- You are familiar with DevOps practices, cloud infrastructure, containerized applications, and Kubernetes fundamentals.
- You have experience with data modeling and schema design.
- You care about high-quality code and engineering practices such as continuous delivery and automated testing.
- You value experimentation, iterative development, and collaborative software development practices.
- You are comfortable navigating ambiguity and open-ended problems, using data and sound judgment to make decisions.
Where You'll Be
- This role is based in London
- 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.
Employment type
Permanent
Your next step
- Have your CV and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the salary range before committing time to the process.
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Source & posting history
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
London
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
- Status in our records
- Active
- First seen by us
- Aug 21, 2026
- Recorded sightings
- 38
- Last seen by us
- Oct 8, 2026
- Employer says posted
- Aug 12, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
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