Analytics Engineer - #2121017

This is an opportunity to make a significant contribution within a unique organizational concept, working from our modern offices in Hamburg/Germany, Stockholm/Sweden or Sofia/Bulgaria.

Join Stillfront as an Analytics Engineer within our distributed Data Platform team. In this role, you will be instrumental in building and maintaining robust data pipelines and analytical solutions to empower group management, hubs (including marketing, ad-monetization, and finance), game studios, and strategic projects.

A key aspect of this role involves collaborating directly with our game studios to understand their unique data needs and identify opportunities to leverage and share group data platform technologies. You will play a crucial part in finding synergies and promoting best practices across the organization.

Operating with open-source principles, the Data Platform is in the exciting early stages of development and collaborates weekly with various stakeholders to elevate data quality and richness. In this role, you will specifically focus end to end from game data integration to working closely with other Analysts to provide data products for data driven decision making.

YOUR MISSION

• Design, build, and maintain scalable ETL/ELT pipelines using modern data tools (e.g., dbt, Airflow, Spark, etc.)
• Develop and maintain data models in our warehouse (e.g., Snowflake, BigQuery, Redshift)
• Monitor data quality, identify issues, and implement fixes or improvements
• Collaborate with cross-functional teams to understand data needs and translate them into technical solutions
• Perform exploratory data analysis and deliver dashboards, reports, and insights to business teams
• Advocate for data governance, documentation, and best practices

YOUR BACKSTORY

• 5+ years of professional experience in the combination of data engineering and analytics
• Passion for building and maintaining strong professional relationships to support effective collaboration in international and multicultural environments
• Proficiency in SQL and Python (or another data-friendly language)
• Well-developed engineering skills with a strong foundation in Git version control
• Experience with cloud data platforms (AWS, GCP, or Azure)
• Familiarity with BI tools like Looker, Tableau, or Power BI
• Experience with data ops or orchestration tools (e.g., dbt, Airflow)
• Strong understanding of data modeling, data warehousing, and ETL design
• Ability to communicate technical concepts clearly to non-technical stakeholders
• A product mindset: you care about the “why” behind the data, not just the “how”

NICE TO HAVE

• Exposure to CI/CD and version control (Git) in a data context
• Familiarity with event tracking, product analytics, or experimentation frameworks