Senior Analytics Engineer
The Freemium R&D team oversees the entire user journey on Spotify and ensures we engage with people in innovative ways, every step of the way. Our team grows Spotify’s audience by finding future listeners around the world and delivering the right value to them, at the right time. With research, product development, product design, engineering, and marketing all collaborating in one organisation, we’re able to quickly create meaningful features and services for millions of people around the world, resulting in joyful, long-lasting relationships with Spotify.
We have ambitious plans in Freemium to build the next generation multi dimensional Commerce platform, and we are looking for an analytics engineer to join the team. You will work with data engineers and data scientists to solve problems in the data space and build the commerce platform’s data platform.
The commerce platform is evolving to cover multiple use cases through multiple monetization models and data sits at the heart of it - by building the commerce data platform, this team will connect data producers with data consumers, through datasets, infrastructure, tooling and expertise. The team plays a pivotal role in identifying the core data gaps across the tribe and advocating for data best practices.
We are looking for an Analytics Engineer who will help us build out a top class analytics ecosystem so that data scientists in the commerce platform team are empowered to focus on gathering insights, building impactful visualisations, and crafting predictive models.
What You'll Do
- Work with data scientists across the commerce-platform / Mercury to identify areas of opportunity and create core analytics datasets
- Evaluate the data quality and performance of our existing pipelines and use these analyses to make meaningful improvements and collaborate with data scientists to build robust pipelines that incorporate standard methodologies
- Promote data engineering methodologies among all data producers within freemium
- Work with development teams to ensure features launch suitably instrumented and monitored
Who You Are
- You have a track record of working in the analytics space and have experience with building robust data models for analytics purposes, reliable testing framework, scalable data warehouse design and an obsession for data quality
- You understand how data consumers’ work (scientists, analysts, business users), how they generate insights from data and how to make their lives easier
- You have a masterful understanding of SQL
- You have experience using git to facilitate effective collaboration between dataset producersYou are able to operate effectively and autonomously across multiple teams in situations of ambiguity, with only high-level direction
- You know how to understand and tackle loosely defined problems and come up with relevant answers and practical insights
- You have strong communication skills and experience working across different teams
- Experience with Python and data tools such as Spark, Hadoop, Airflow, Luigi Apache Beam, Dataflow, DBT and Great Expectations is a bonus!
Where You'll Be
- We are a distributed workforce enabling our band members to find a work mode that is best for them!
- Where in the world? For this role, it can be within the EMEA region in which we have a work location
- Prefer an office to work from home instead? Not a problem! We have plenty of options for your working preferences. Find more information about our Work From Anywhere options here.
- Working hours? We operate within the Central European time zone for collaboration
- We ask that our team members be located within Greenwich Mean time zone, Central European time zone, or Eastern European standard time zone for the purposes of our collaboration hours