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Senior Analytics Engineer - Personalization

extra holidays - extra parental leave

Remote:

Full Remote

Contract:

Full time

Experience:

Senior (5-10 years)

Work from:

United Kingdom, Sweden

Offer summary

Qualifications:

Extensive experience in analytics engineering or data science., Strong expertise with dbt and cloud platforms., Proficient in SQL, data modeling, and pipeline management., Experience mentoring on data management best practices..

Key responsabilities:

Develop data and pipeline strategies for reliable access.
Design and maintain efficient data pipelines and models.

Spotify Music XLarge http://www.lifeatspotify.com/

5001 - 10000 Employees

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Job description

We are seeking a Senior Analytics Engineer to join our Personalization Surfaces Data Science team, which supports personalization and insights across our user-facing surfaces, including the Home, Search, and Promotions platform. These surfaces are critical entry points for hundreds of millions of users, and the team’s work directly influences how users discover and engage with personalized content.

In this role, you will lead the team’s data and pipeline strategy, ensuring data scientists have reliable and efficient access to the datasets and metrics they need. You will collaborate with data engineering and platform teams across the organization to improve data quality, streamline workflows, and scale best practices for data management. You’ll design and implement scalable data pipelines and enable efficient use of internal and external datasets. Your ability to unlock efficiencies and improve data accessibility will be pivotal to delivering faster, deeper insights that shape the user experience on Home, Search, and Promotions surfaces.

What You'll Do

Develop and implement a data and pipeline strategy that ensures scalable, reliable access to high-quality datasets and metrics.

Design and, with the technically skilled data science team, build and maintain efficient data pipelines and models using tools like dbt and Google Cloud.

Collaborate with data engineering teams and platform partners to enhance data usability, reliability, and scalability for key business use cases.

Partner with data scientists to develop robust metrics and implement automated metrics monitoring via dashboards or other tools.

Lead the implementation of data management benchmarks, reducing time spent on data wrangling and enabling data scientists to focus on impactful analyses.

Streamline access to critical datasets and metrics that power personalization and recommendations on key product surfaces.

Identify and implement opportunities to improve workflows and eliminate redundant or manual data management tasks.

Act as a data strategist, empowering the Data Science team to better use internal and external data assets.

Who You Are

You have extensive experience in analytics engineering, data engineering, data science, or a related field, with a focus on enabling data-driven decision-making in a fast-paced organization.

You have strong expertise with dbt (or similar) and are proficient in SQL, data modeling, and building/managing scalable data pipelines in cloud-based environments (e.g., Google Cloud Platform, AWS).

You have a proven track record of working cross-functionally with data scientists, data engineers, and product teams to enhance data workflows and usability.

You are a strategic problem solver who can identify inefficiencies in data processes and implement solutions that drive measurable impact.

You have experience mentoring and guiding teams on best practices for data management and utilization.

You possess excellent collaboration and communication skills, with the ability to influence and align teams across different organizational levels.

Where You'll Be

This role can be based in our Stockholm or London office.