As a Senior Data Analyst on our Growth team, you will play a key role in taking our marketing performance to new heights. You will work closely with User Acquisition and Growth partners to analyze data, find opportunities, and deliver actionable insights. Work closely with UA and Growth partners to understand performance, investigate business questions, and provide actionable recommendations.

Lead analytics projects end to end, from problem definition and data exploration to communicating insights and collaborating. Own the business logic and analytical requirements for Growth data models, ensuring they accurately represent how the company measures performance. Act as a key partner to Data Engineering, translating business and analytical needs into clear data requirements and validating delivered solutions.

Proactively identify and investigate quality issues, inconsistencies, and gaps in Growth reporting and underlying data models. Build and maintain scalable reporting and analytics solutions, reducing repetitive manual analysis where possible. Define and maintain key Growth metrics and measurement logic across areas such as spend, acquisition, revenue, attribution, and marketing performance.

Conduct in-depth analysis to understand performance drivers, find opportunities, and support investment decisions. Clearly communicate complex findings to both technical and non-technical partners, including senior leadership. Work closely with Data Scientists on measurement, experimentation,



and modeling projects by providing strong analytical and data foundations. ??????????: More than 4 years of professional experience in Data Analytics, Business Intelligence, Analytics Engineering, or a related role.

Strong experience independently delivering analytics projects and working directly with business partners.

Experience owning or significantly contributing to analytical data models, metric definitions, or reporting foundations. Advanced SQL skills and strong experience working with large, complex datasets. Proficiency in Python for data analysis, automation, and analytics workflows. Strong understanding of data modeling, data quality, and analytical data structures.

Experience translating business requirements into data requirements and working closely with Data Engineering teams. Proficiency in data visualization/BI tools such as Looker, Tableau, or similar. Good understanding of statistical analysis and experimentation.

Great attention to detail and high standards for data accuracy and reliability. Strong collaboration skills, able to work effectively across Analytics, Data Science, Data Engineering, and business teams. Familiarity with digital marketing data, attribution metrics, and acquisition is a great advantage ???????: Our approach is based on a pay-for-performance philosophy, rewarding individual impact. other local benefits or benefits established by applicable law #

📌 Data Analyst In Gaming (Barcelona)
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