Data Engineer - Personalization (Search)
The Personalization (PZN) team makes deciding what to play next on Spotify easier and more enjoyable for every listener. We seek to understand the world of music, podcasts and audiobooks better than anyone else so that we can make great recommendations to every individual and keep the world listening. Every day, hundreds of millions of people all over the world use the products we build which include destinations like Home and Search as well as original playlists such as Made For You, Discover Weekly and Daily Mix.
We are looking for Data Engineers to join our teams across PZN. You’ll be able to grow your skills in engineering at scale, drive long term platform vision, and join a high-energy, positive team environment!
What You'll Do
Work with large-scale data pipelines with data processing frameworks like Scio, BigQuery, Google Cloud Platform and Apache Beam.
Develop, deploy, and operate Java services that impact millions of users.
Work towards supporting machine learning projects powering the experience that suits each user individually.
Collaborate with other engineers, product managers and stakeholders, taking on learning and leadership opportunities that will arise every single day.
Deliver scalable, testable, maintainable, and high-quality code.
Share knowledge, promote standard methodologies, making your team the best version of itself through mentorship and constructive accountability.
Who You Are
You are familiar with the concepts of data modeling, data access, and data storage techniques.
You are familiar with distributed data processing frameworks (ex: Beam, Spark).
You want to work on a team employing agile software development processes, data-driven development, and responsible experimentation.
You value opportunities to work collaboratively.
Where You'll Be
We offer you the flexibility to work where you work best! For this role, you can be within the EMEA region as long as we have a work location (excluding France due to on-call restrictions).
This team operates within the Central European and GMT time zone for collaboration.
About the job
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Data Engineer - Personalization (Search)
The Personalization (PZN) team makes deciding what to play next on Spotify easier and more enjoyable for every listener. We seek to understand the world of music, podcasts and audiobooks better than anyone else so that we can make great recommendations to every individual and keep the world listening. Every day, hundreds of millions of people all over the world use the products we build which include destinations like Home and Search as well as original playlists such as Made For You, Discover Weekly and Daily Mix.
We are looking for Data Engineers to join our teams across PZN. You’ll be able to grow your skills in engineering at scale, drive long term platform vision, and join a high-energy, positive team environment!
What You'll Do
Work with large-scale data pipelines with data processing frameworks like Scio, BigQuery, Google Cloud Platform and Apache Beam.
Develop, deploy, and operate Java services that impact millions of users.
Work towards supporting machine learning projects powering the experience that suits each user individually.
Collaborate with other engineers, product managers and stakeholders, taking on learning and leadership opportunities that will arise every single day.
Deliver scalable, testable, maintainable, and high-quality code.
Share knowledge, promote standard methodologies, making your team the best version of itself through mentorship and constructive accountability.
Who You Are
You are familiar with the concepts of data modeling, data access, and data storage techniques.
You are familiar with distributed data processing frameworks (ex: Beam, Spark).
You want to work on a team employing agile software development processes, data-driven development, and responsible experimentation.
You value opportunities to work collaboratively.
Where You'll Be
We offer you the flexibility to work where you work best! For this role, you can be within the EMEA region as long as we have a work location (excluding France due to on-call restrictions).
This team operates within the Central European and GMT time zone for collaboration.