Analytics Engineer - User Platform

About the Role: Analytics Engineer - User Platform at Spotify

User Platform (UP) is a crucial studio within Spotify’s Platform mission, responsible for authentication, authorization, user account data, and user experience configuration. UP's mission is to provide a secure platform that enables users to establish their identities and manage account data across various surfaces, while also empowering internal teams to experiment and customize the user experience. This studio manages core services essential for Spotify to function and deliver audio experiences to over 700 million users globally.

We are seeking a talented and engaged data analytics engineer to support teams building foundational data infrastructure for user access and identity management insights. Your work will directly enable teams to identify user friction, accurately measure conversions, and continuously optimize the initial Spotify experience.

What You'll Do

• Define and optimize the IAM Domain Data Schema, ensuring an efficient and scalable data structure, addressing gaps, and proposing improvements to meet domain needs.
• Collaborate with Engineering Teams to establish event instrumentation requirements, ensuring the collection of accurate and actionable data.
• Lead long-term internal initiatives focused on data infrastructure, quality, technical health, and champion data-informed decision-making and new operational approaches across the organization.
• Guide engineering teams in developing cohesive data models that unify disparate data sources, creating an ecosystem of analysis-friendly datasets for research and and analytics.
• Design, implement, and maintain high-quality datasets and data pipelines using DBT, Python, and SQL on BigQuery and GCS.
• Collaborate closely with engineers, data scientists, and team leads across the mission to design and promote shared methodologies for data-informed decisions within R&D.

Who You Are

• You possess a proven track record in developing data products using SQL and/or Python.
• You have experience translating open-ended analytics goals into production-quality datasets.
• You are knowledgeable in data modeling, data access, and data storage techniques.
• You are comfortable stepping through ETL processes and tracing data flows through DAGs, and you are experienced with DBT or similar tools.
• You demonstrate strong proficiency using SQL in cloud data warehouses (e.g., BigQuery, Redshift, Snowflake). Experience with GCP tooling is a significant plus.
• You are a communicative individual who values building strong relationships with colleagues and partners, and enjoys mentoring and teaching others.
• You can operate effectively and autonomously across multiple teams in ambiguous situations, with only high-level direction.
• You are committed to improving data quality through testing, tooling, and continuous performance evaluation.

Where You'll Be

This role is based in London or Stockholm. We offer flexibility to work where you work best, though some in-person meetings will be required, allowing for a hybrid work arrangement.

Key skills/competency

• SQL
• Python
• DBT
• BigQuery
• Data Modeling
• ETL
• Data Infrastructure
• Data Quality
• Event Instrumentation
• GCP