Analytics Engineer

Acne Studios is a progressive luxury house and through collaboration and curiosity, we set high aspirations and strive for excellence. We value everyone's contribution and embrace feedback to develop ourselves and others. We aim to minimise our environmental impact across all our operations and to address societal challenges in the way we conduct our business.

As Analytics Engineer at our Stockholm Head Office, you will transform clean, validated data into well-documented, trusted datasets that teams across Acne Studios rely on. Your work enables self-service analytics through Power BI and other consumption layers, so that business users can find and use data without ad-hoc engineering support. You succeed when datasets are accurate and trusted, and when metrics are consistent across the company. To get there, you build strong relationships with stakeholders, communicate clearly, deliver reliably and share your knowledge with the team.

CULTURE OF COLLABORATION

We firmly believe that when you feel supported, included, and trusted, it enables you to enjoy your work and thrive in it. You will be a part of a team of colleagues with diverse roles and backgrounds, each with their unique skills and experiences.

WHAT YOU WILL DO

As Analytics Engineer your main contribution will be to build the data foundation that turns raw, validated data into business-ready models used across the company. You will report to Manager Data Insights. You will play a vital role in making data accessible, reliable and consistent for everyone at Acne Studios by:

Designing and maintaining dimensional models (facts, dimensions, lookups) in the gold layer, following star schema principles

Building and operating reusable data transformation pipelines using PySpark and SQL on Databricks

Structuring and exposing data for consumption by Power BI and external systems such as Centric and Dema

Contributing to building a centralized semantic layer in Databricks

Implementing and maintaining core business metrics, logic and KPIs

Ensuring data quality through automated testing and validation

Documenting datasets and making them easy to find and use

Partnering with stakeholders to translate business needs into requirements and data models

Supporting analysts working in Power BI and Databricks Dashboards with clear and structured guidance

Communicating proactively with business users about what data is available, what it means and how to use it

Contributing to improvements in transformation patterns, testing frameworks, tools and ways of working

WHO YOU ARE

You have high aspirations and focus on details that create substantial impact. You enjoy working as a team and you embrace feedback to develop yourself and others. You are curious and thrive in a dynamic environment. Cooperation, respect, and clear communication are important, along with your ambition to learn and grow. If these qualities speak to you, we would love to have you on our team.

Specific personal qualities for this role:

Clear communicator with both technical and business audiences

Service-minded and responsive

Structured and detail-oriented, with high standards for accuracy and documentation

Proactive in identifying improvements

Curious and motivated to keep learning

Team player who shares knowledge through code reviews, demos and presentations

Specific experience and knowledge for this role:

Strong dimensional modelling skills (star schema, SCD2 etc.)

Advanced PySpark and SQL (window functions, complex joins, incremental processing)

Experience working with Spark

Solid Python skills (data validation, scripting, testing)

Experience with the Databricks platform: Delta Lake, Unity Catalog, notebooks, jobs, workflows

Experience with orchestration tools (Databricks Workflows, Data Factory or similar)

Familiarity with Power BI (semantic models, relationships, DAX basics)

Familiarity with AI-assisted Lakehouse tools (code assistants, Genie spaces, AI/BI dashboards, model serving endpoints)

Familiarity with CI/CD for data assets (Databricks Asset Bundles, Git integration)

Familiarity with data quality frameworks (Great Expectations or custom assertion patterns)

Fluent in English

What matters most to us is not whether you master all the listed knowledge and skills. We are dedicated to recognising the potential in each individual. We embrace diversity of people as well as ideas and viewpoints and encourage everyone's individual expression of their own identity.