Spotify

Platform

AnalyticsEngineerII

stockholm, stockholm, sweden; London, United Kingdom Permanent Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Mid candidates.

The Brief

“Analytics Engineer II at Spotify. Skills: analytics engineering, data engineering, dbt, SQL, cloud data warehouse, data modelling, BI/visualisation tools. Build and maintain analytical data models using dbt (or similar SQL-based transformation frameworks) in BigQuery for a broad set of stakeholders. Build and operate reliable data pipelines using SQL, with a focus on testing, observability, and CI/CD”

What You'll Achieve.

enable Spotify to learn quickly and scale easily; welcome a billion customers; build and maintain trusted analytical models, metrics, and data products that power developer productivity, platform health, and leadership decision-making; translate platform signals into reliable, well-modeled data assets that help Spotify ship faster and safer; enable better decision-making across teams

Industry & Context.

Platform
Problems you'll solve

troubleshooting

What They're Looking For.

Must Have

2+ years of experience in analytics engineering, data engineering, or a related field, SQL skills, experience with data modelling, experience with dbt (or similar SQL-based transformation frameworks), experience with a cloud data warehouse such as BigQuery, Snowflake, Redshift, or Databricks SQL, familiar with workflow orchestration tools such as Airflow, Dagster, Prefect, or Flyte, care about data quality, reliability, and testability, comfortable working with BI/visualisation tools such as Looker or Tableau, communicate clearly with both technical and non-technical partners, able to prioritize and deliver in a fast-moving environment

Nice to Have

experience with platform or developer productivity data, experimentation, or ML/AI metrics

What You'll Do.

Build and maintain analytical data models using dbt (or similar SQL-based transformation frameworks) in BigQuery for a broad set of stakeholders

Build and operate reliable data pipelines using SQL

with a focus on testing

Help define and evolve key metrics for platform health

developer productivity

and ML/AI platform adoption

Partner with Data Engineers on upstream pipelines and collaborate with Product

and Data Science to scope and deliver insights

and cost efficiency across pipelines and models

including troubleshooting and backfills

Contribute to dashboards and self-serve data products that enable better decision-making across teams

Follow and contribute to data quality

and documentation practices across the analytics layer

Participate in a fair support rotation for key datasets

and analytical products

How You'll Work.

Team & Collaboration

Working closely with Data Engineers, Product, Engineering, and Platform partners; Partner with Data Engineers on upstream pipelines and collaborate with Product, Engineering, and Data Science to scope and deliver insights; communicate clearly with both technical and non-technical partners

Communication Scope

communicate clearly with both technical and non-technical partners

Process & Methodology

able to prioritize and deliver in a fast-moving environment

Full Job Description

## Description The Platform team creates the technology that enables Spotify to learn quickly and scale easily, enabling rapid growth in our users and our business around the globe. Spanning many disciplines, we work to make the business work; creating the infrastructure, tooling, frameworks, and capabilities needed to welcome a billion customers. We’re looking for an Analytics Engineer II to join Spotify's Platform Central Data (PCD) squad, a cross-functional Data Engineering and Analytics Engineering team within the Platform Mission. You’ll help build and maintain trusted analytical models, metrics, and data products that power developer productivity, platform health, and leadership decision-making. Working closely with Data Engineers, Product, Engineering, and Platform partners, you’ll translate platform signals into reliable, well-modeled data assets that help Spotify ship faster and safer. ## What You"ll Do Build and maintain analytical data models using dbt (or similar SQL-based transformation frameworks) in BigQuery for a broad set of stakeholders Build and operate reliable data pipelines using SQL, with a focus on testing, observability, and CI/CD Help define and evolve key metrics for platform health, developer productivity, and ML/AI platform adoption Partner with Data Engineers on upstream pipelines and collaborate with Product, Engineering, and Data Science to scope and deliver insights Improve data quality, performance, and cost efficiency across pipelines and models, including troubleshooting and backfills Contribute to dashboards and self-serve data products that enable better decision-making across teams Follow and contribute to data quality, testing, and documentation practices across the analytics layer Participate in a fair support rotation for key datasets, pipelines, and analytical products ## Who You Are You have 2+ years of experience in analytics engineering, data engineering, or a related field You have strong SQL skills and experience with

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