Spotify

Analytics Engineer II – User Platform

Spotify

full-time

Posted on:

Location Type: Hybrid

Location: London • United Kingdom

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Tech Stack

Amazon RedshiftBigQueryCloudETLGoogle Cloud PlatformPythonSQL

About the role

  • Define and optimize the IAM Domain Data Schema to ensure the most efficient and scalable data structure, addressing gaps and proposing improvements to support the domain's needs.
  • Collaborate with Engineering Teams to set event instrumentation requirements and ensure the collection of accurate and actionable data.
  • Lead long-term internal initiatives focused on data infrastructure, quality, technical health, and promoting data-informed decision-making and new ways of working 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 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.

Requirements

  • You have a track record of experience in the development of data products (using SQL and/or Python)
  • You have a track record of taking open-ended analytics goals and translating them 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 other similar tools.
  • You have strong proficiency using SQL in cloud data warehouses (e.g. BigQuery, Redshift, Snowflake). Experience with GCP tooling is a plus
  • You are a communicative person who values building strong relationships with colleagues and partners and enjoys mentoring and teaching others
  • You are able to operate effectively and autonomously across multiple teams in situations of ambiguity, with only high-level direction
  • Improve data quality through testing, tooling and continuously evaluating performance
Benefits
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Applicant Tracking System Keywords

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Hard Skills & Tools
data modelingdata access techniquesdata storage techniquesETL processesdata pipelinesDBTPythonSQLBigQueryGCS
Soft Skills
communicationrelationship buildingmentoringteachingautonomyoperating in ambiguitycollaborationleadershipdecision-makingproblem-solving