Analytics Engineer: Build Trusted Data for Self-Service BI

Acne-Studios-Ab; Stockholms kommun; On-site; SEK 700,000 - 1,100,000; Full time

Job summary

Acne Studios Stockholm Head Office seeks an Analytics Engineer to transform clean data into trusted datasets and enable self-service analytics via Power BI and Databricks. You will build and maintain data foundations, models, and metrics, partnering with stakeholders to translate business needs into robust data solutions.

You will design dimensional models, develop data pipelines with PySpark and SQL, and ensure data quality through automated tests while documenting datasets for easy access and

Qualifications

• Advanced PySpark and SQL experience with complex transforms.
• Experience with Spark and Databricks platform (Delta Lake, Unity Catalog).
• Familiarity with Power BI semantic models and DAX basics.
• Knowledge of data quality frameworks and CI/CD for data assets.

Responsibilities

• Build the data foundation turning raw, validated data into business-ready models.
• Design and maintain dimensional models in the gold layer following star schema.
• Create reusable data transformations with PySpark and SQL on Databricks.
• Expose data for consumption by Power BI and external systems.
• Contribute to a centralized semantic layer in Databricks.
• Implement and maintain core business metrics and KPIs.
• Ensure data quality via automated testing and validation.
• Document datasets and enable easy discovery and use.
• Collaborate with stakeholders to translate needs into data models.
• Support analysts with guidance for Power BI and Databricks dashboards.

Skills

PySpark

SQL

Spark

Databricks

Power BI

Delta Lake

Unity Catalog

CI/CD

Data quality

Tools

Databricks

Power BI

Delta Lake

Unity Catalog

Git integration

Job description

Acne Studios Stockholm Head Office seeks an Analytics Engineer to transform clean data into trusted datasets and enable self-service analytics via Power BI and Databricks. You will build and maintain data foundations, models, and metrics, partnering with stakeholders to translate business needs into robust data solutions.

You will design dimensional models, develop data pipelines with PySpark and SQL, and ensure data quality through automated tests while documenting datasets for easy access and