Why This Job is Featured on The SaaS Jobs
This Analytics Engineer II role stands out in SaaS because it sits at the intersection of product platform operations and data, focusing on how a large-scale platform learns, ships, and stays reliable. Rather than supporting a single customer-facing feature, the remit centers on platform health and developer productivity signals, which are increasingly critical as SaaS businesses mature and internal platform teams become accountable for measurable outcomes.
From a career perspective, the work builds durable SaaS skills in metric design, governed semantic layers, and trusted data products that multiple teams depend on. Experience with dbt-style transformations, warehouse-first modeling, and CI/CD-minded analytics maps well to modern SaaS data stacks, especially where reliability, observability, and cost discipline matter as much as insight generation. The cross-functional nature of partnering with engineering, product, and leadership also strengthens the ability to translate technical telemetry into decision-grade reporting.
This role is best suited to someone who enjoys turning ambiguous platform questions into clear definitions and repeatable models, and who is comfortable owning data quality over time. It will fit professionals who prefer stakeholder-heavy work and like operating in a supportable, well-instrumented analytics environment.
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.
