Staff Data Engineer – Subscriptions User Understanding

Spotify

Staff Data Engineer driving data engineering strategy for Spotify's subscription analytics. Leading architecture decisions and improving data solutions for user engagement and growth.

Posted 7/27/2026full-timeRemote • 🇬🇧 United KingdomLeadWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and operating large-scale cloud-native data platforms, with a focus on data modeling, governance, and quality practices. Proven ability to mentor engineers and lead architectural decisions that enhance scalability and reliability across data ecosystems.

Highest-signal resume keywords

Cloud-Native Data PlatformsDistributed Data PipelinesData ModelingData GovernanceMentoring Engineers

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data EngineeringData Quality PracticesData ArchitectureBatch ProcessingStreaming Data PlatformsSQLPythonBigQueryDataflowScio

Soft Skills

Effective CommunicationMentoringCollaborationTechnical GuidanceContinuous Improvement

Tools & Technologies

GCSCloud-Native ToolsAnalytics PlatformsMachine Learning FrameworksObservability Tools

Industry Keywords

Data Engineering StrategyScalabilityReliabilityOperational ExcellenceTechnical Debt

Tech Stack

Tools & technologies

BigQueryCloudPythonSQL

About the role

Key responsibilities & impact

Define and drive the long-term data engineering strategy for the Subscriptions User Understanding domain, identifying opportunities that improve scalability, reliability, and business impact.
Design scalable batch and streaming data platforms that power analytics, experimentation, machine learning, and subscriber experiences.
Partner with Product, Engineering, Data Science, Analytics, and Platform teams to turn complex business challenges into durable, well-designed data solutions.
Lead architectural decisions and establish engineering best practices for data quality, governance, observability, reliability, and operational excellence across multiple squads.
Design data models and platform architecture that support sustainable growth toward one billion users while balancing performance, cost, and maintainability.
Simplify complex systems, reduce technical debt, and improve the developer experience across the broader data ecosystem.
Mentor senior engineers, influence technical direction through collaboration, and help foster a culture of thoughtful engineering, knowledge sharing, and continuous improvement.

Requirements

What you’ll need

Extensive experience designing, building, and operating large-scale cloud-native data platforms.
Deep experience building reliable distributed data pipelines using technologies such as Scio, BigQuery, Dataflow, GCS, SQL, Python, or similar cloud-native tools.
Strong understanding of modern data modeling, metadata management, governance, and data quality practices.
Ability to balance immediate business needs with long-term architectural sustainability.
Effective communication with engineers, product managers, data scientists, analysts, and senior leadership.
Enjoy mentoring engineers and helping technical teams grow through coaching, technical guidance, and thoughtful feedback.

Benefits

Comp & perks

Flexible work arrangements