Data Analytics Engineer for Growth & Insights

Vitamin Well Group; Stockholms kommun; On-site; SEK 520,000 - 640,000; Full time

Job summary

Vitamin Well Group is building its Data & Analytics team to shape the digital business. The Data Analyst will work across the full data lifecycle, turning data into trusted insights for cross-functional teams including Marketing, Sales and Product.

You will develop reusable models and dashboards, strengthen data quality, and collaborate with Engineering on instrumentation and data governance, using AI-native tools to accelerate insights.

Qualifications

• Bachelor's degree in Software Engineering, IT, Business or a related field.
• 1–4 years of professional experience in Analytics Engineering, Data Analysis or a similar role.
• Experience across data journey from raw data to analysis and business application is preferred.

Responsibilities

• Build and maintain reliable data models and transformations with data quality focus.
• Develop data pipelines and integrations across our digital data ecosystem.
• Create dashboards and self-serve analytics for global and local teams to access KPIs.
• Translate business questions into structured models, analysis and actionable insights.
• Analyze customer behavior and growth across funnel areas like acquisition and retention.
• Collaborate with Product and Engineering on event instrumentation and schema design.
• Contribute to data governance, documentation and best practices, using AI-native tools.

Skills

SQL

Data Modelling

Python

APIs

BI Tools

Data Lakes/ETL

AI-native coding tools

Swedish & English

Education

Bachelor's degree in Software Engineering / IT / Business or related field

Tools

dbt

Dataform

SQLMesh

GCP

Azure

AWS

Snowflake

Databricks

Airflow

Job description

Vitamin Well Group is building its Data & Analytics team to shape the digital business. The Data Analyst will work across the full data lifecycle, turning data into trusted insights for cross-functional teams including Marketing, Sales and Product.

You will develop reusable models and dashboards, strengthen data quality, and collaborate with Engineering on instrumentation and data governance, using AI-native tools to accelerate insights.