spotify - Analytics Engineer - User Platform

London / Stockholm5mo ago

Remote EMEA Music Streaming Analytics Engineer Forester SQL Team Management Decision Making Python

Requirements

• Skills needed: Data analytics engineer with experience in defining and optimizing IAM Domain Data Schema; collaboration skills for setting event instrumentation requirements. • Years of experience: Not explicitly stated. • Education: Not explicitly stated. • Certifications: None mentioned, but a track record suggests relevant qualifications may exist (not specified). • Must-haves: Experience with DBT and SQL on BigQuery and GCS; ability to guide engineering teams in developing cohesive data models that unify disparate data sources for research and analytics.

Responsibilities

• Define and optimize the IAM Domain Data Schema to ensure efficient and scalable data structure for user access and identity management insights. • Collaborate with Engineering Teams on event instrumentation requirements to collect accurate and actionable data. • Lead long-term internal initiatives focused on improving data infrastructure, quality, technical health, and promoting a culture of data-informed decision making across the organization. • Guide engineering teams in developing cohesive data models that unify disparate data sources to create an ecosystem for analysis within R&D. • Design, implement, and maintain high-quality datasets and data pipelines using DBT, Python, SQL on BigQuery, and GCS. • Collaborate closely with engineers, data scientists, and team leads across the mission in designing shared methodologies to make data-informed decisions within R&D.

Benefits

• Collaboration with Engineering Teams to set event instrumentation requirements and ensure the collection of accurate data for user access insights. • Lead long-term internal initiatives focused on improving data infrastructure quality, technical health, and promoting a culture of data-informed decision making within Spotify's organization. • Engage in guiding engineering teams to develop cohesive data models that unify disparate sources for better research and analytics capabilities. • Design, implement, and maintain high-quality datasets and pipelines using DBT, Python, SQL on BigQuery, and GCS as part of the job responsibilities.