Why This Job is Featured on The SaaS Jobs
This Analytics Engineer II role stands out because it sits close to the operational core of a large-scale SaaS platform, where measurement is part of how the product is built and run. The remit spans platform health, developer productivity, and adoption signals, which are increasingly central concerns for SaaS organisations that depend on internal platforms to ship reliably and efficiently.
From a career perspective, the work builds durable SaaS data engineering instincts: defining metrics that teams will actually use, creating trusted models in a modern analytics stack, and treating the analytics layer as production software with testing, CI/CD, and observability. Exposure to cross-functional stakeholders also strengthens the ability to translate ambiguous platform questions into stable data products, a transferable skill across SaaS companies with mature data practices.
The role is best suited to someone who enjoys ownership of data quality and semantics, not just reporting outputs. It will fit professionals who like collaborating with engineers and product partners, are comfortable operating pipelines over time through support rotations, and want their analytics work to influence platform decisions rather than only business KPIs.
The section above is editorial commentary from The SaaS Jobs, provided to help SaaS professionals understand the role in a broader industry context.
Job Description
Mission Statement
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.
About the Team
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.
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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 data modelling
- You are experienced with dbt (or similar SQL-based transformation frameworks) and a cloud data warehouse such as BigQuery, Snowflake, Redshift, or Databricks SQL
- You are familiar with workflow orchestration tools such as Airflow, Dagster, Prefect, or Flyte
- You care about data quality, reliability, and testability
- You are comfortable working with BI/visualisation tools such as Looker or Tableau
- You communicate clearly with both technical and non-technical partners
- You are able to prioritize and deliver in a fast-moving environment
- You have experience with platform or developer productivity data, experimentation, or ML/AI metrics
Where You'll BeThis role is based in London or Stockholm.
We offer you the flexibility to work where you work best! There will be some in person meetings, but still allows for flexibility to work from home.
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Spotify is an equal opportunity employer. You are welcome at Spotify for who you are, no matter where you come from, what you look like, or what’s playing in your headphones. Our platform is for everyone, and so is our workplace. The more voices we have represented and amplified in our business, the more we will all thrive, contribute, and be forward-thinking! So bring us your personal experience, your perspectives, and your background. It’s in our differences that we will find the power to keep revolutionizing the way the world listens.
At Spotify, we are passionate about inclusivity and making sure our entire recruitment process is accessible to everyone. We have ways to request reasonable accommodations during the interview process and help assist in what you need. If you need accommodations at any stage of the application or interview process, please let us know - we’re here to support you in any way we can.
