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Kry is Europe's leading digital healthcare platform, enabling patients to access doctors, nurses, and psychologists online within minutes. The company combines digital and physical care to transform healthcare access for millions of patients across Europe.
You'll join the Analytics team as an Analytics Engineer, working across the full analytics workflow—from building robust data pipelines to delivering insights that drive business decisions. The role balances data engineering and analytics work intentionally, suiting someone a few years into their data career who enjoys both writing clean code and uncovering what the numbers mean.
Key responsibilities include:
- Building, testing, and maintaining data pipelines and models using dbt, orchestrated with Dagster
- Setting up new data flows and ensuring data reliability, documentation, and usability
- Maintaining the business operations model that tracks key metrics and flagging anomalies
- Building dashboards in Looker and developing LookML
- Conducting analyses ranging from quick questions to deep dives, presenting findings to stakeholders in marketing, operations, product, and finance
- Designing and evaluating A/B tests using SQL and Python
Your first months will focus on learning the data landscape, tech stack, and team processes with full support. The role offers growth opportunities across analytics, data engineering, data science, or becoming a domain expert in healthcare operations, product, marketing, or finance.
The Analytics team spans Sweden, France, and the UK, working with data from tech products and healthcare operations across Europe. You'll work from a central Stockholm office with a flexible hybrid remote policy.
Requirements:
- 1–5 years of hands-on experience in a data role (data analyst, analytics engineer, BI developer, or data engineer)
- Solid SQL skills and understanding of data modeling
- Experience building data pipelines or data models, ideally with dbt
- Working knowledge of Python
- Ability to explain technical work and findings clearly to non-technical colleagues
- Structured, curious mindset with comfort switching between building and analyzing
- Fluent in English (working language)
Nice to have:
- Experience with Dagster or other orchestration tools (Airflow, Prefect)
- Experience with Looker and LookML, or other BI tools (Tableau, Power BI)
- Familiarity with Git, code review, and CI in a data setting
- Experience with A/B testing or statistics
- Background in marketing, product, or healthcare data
- Degree in a quantitative field (engineering, computer science, statistics, economics)
