Senior Data Platform Engineer - Scale Data & Personalization

Spotify; Greater London; Hybrid; GBP 70,000 - 95,000; Full time

Job summary

Spotify in London is seeking an experienced Data Engineer to join the Data Platform. You will collaborate with product and engineering teams to build data infrastructure and datasets, and design systems that handle large-scale user behaviour data.

You will power personalization and recommendations by ensuring reliable data pipelines, modeling data and maintaining scalable architectures. Some in-person meetings will occur with flexible work-from-home options, fitting a hybrid setup.

Qualifications

• Experienced Data Engineer with backend Java development
• Proficient in SQL and BigQuery
• Experience with JVM data processing frameworks (Flink, Beam, Dataflow, Spark)
• Familiar with DevOps, cloud infra, containers and Kubernetes fundamentals
• Experience in data modeling and schema design
• Commitment to high-quality code and CI/CD practices
• Comfort with experimentation, iteration and collaborative development
• Able to navigate ambiguity and use data-driven judgment

Responsibilities

• 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.
• Power personalization and recommendation systems with reliable data pipelines.
• Design and evolve data architectures to support high data volumes and diverse internal users.
• Improve reliability, scalability, and usability of data infrastructure.
• Work across disciplines to solve complex data challenges and make an impact across Spotify.

Skills

Java

SQL

Data Modeling

CI/CD

Kubernetes

DevOps

Ambiguity handling

Tools

BigQuery

Spark

Flink

Beam

Dataflow

Job description

Spotify in London is seeking an experienced Data Engineer to join the Data Platform. You will collaborate with product and engineering teams to build data infrastructure and datasets, and design systems that handle large-scale user behaviour data.

You will power personalization and recommendations by ensuring reliable data pipelines, modeling data and maintaining scalable architectures. Some in-person meetings will occur with flexible work-from-home options, fitting a hybrid setup.