Senior Data Analyst (Marketing)

Our requirements

• Advanced SQL - complex queries, aggregations, window functions feel natural to you.
• Working proficiency in at least one BI tool (Tableau preferred; Looker or Power BI also welcome).
• Familiarity with Python for analytics (data manipulation, exploratory analysis, basic modeling).
• A proactive communication style - you keep stakeholders informed without being asked, and you raise your hand when priorities need to shift.
• The ability to ask the right business question before reaching for a methodology, and you're willing to challenge your own assumptions when the data tells a different story.
• Confidence presenting findings to senior stakeholders - you adapt your language to the audience and enjoy making complex things simple.
• Proficiency in translating complex analyses into clear, compelling narratives for non-technical audiences - and those conversations energize you rather than drain you.
• Thrive in fast-paced, ambiguous environments where priorities shift, ownership is expected, and no one needs to tell you what to work on next.

Optional

• Hands-on experience in mobile gaming, mobile apps, or e-commerce (especially around UA or growth analytics).
• Familiarity with incrementality testing, ROAS modelling, or LTV/payback curve analysis
• Knowledge of Databricks or similar data lakehouse environments.
• Any applied use of AI or ML tools in an analytics workflow.
• A genuine habit of staying current - papers you've read, tools you've experimented with, something you learned and actually applied.
• Passion for mobile games, understanding player behavior, and modeling game economy.

Your responsibilities

• Build and own analyses that answer the big Marketing questions: Is our spend efficient? Where should we double down? What's driving a drop in player acquisition?
• Design and maintain dashboards that give Marketing stakeholders a clear, always-on view of performance - and flag anomalies before anyone asks.
• Proactively identify opportunities and problems in data, propose solutions, and drive initiatives end-to-end - from a vague business question all the way to a stakeholder presentation
• Collaborate daily with UA, ASO, Creatives, Data Science, and Product - being the analytical backbone that connects them.
• Translate complex findings into clear, actionable recommendations that non-data audiences can quickly understand and confidently act upon.
• Contribute to automation that reduces recurring manual work and frees the team for higher-value analysis.

About the project

Benefits

• sharing the costs of sports activities
• private medical care
• life insurance
• flexible working time
• fruits
• integration events
• dental care
• no dress code
• video games at work
• coffee / tea
• drinks
• parking space for employees
• leisure zone
• redeployment package
• christmas gifts
• employee referral program