Senior/Lead Data Analyst - Marketing in Winit Germany GmbH, Bremen at Jobgether

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior/Lead Data Analyst - Marketing based in Germany.

Take on a strategic analytics role where data drives marketing performance and business transformation across multiple markets. As a Senior/Lead Data Analyst, you will work at the intersection of marketing, business strategy, and data engineering, delivering insights that shape decision-making and support large-scale integration initiatives. Collaborating with cross-functional teams, you will build scalable reporting solutions, optimize marketing analytics, and help harmonize data across diverse business environments. This position offers the opportunity to influence executive-level decisions while leveraging modern analytics platforms, cloud technologies, and AI-powered workflows. Working in a fully remote, international environment, you will contribute to high-impact projects while helping advance data-driven marketing excellence.

• Drive marketing analytics initiatives by delivering actionable insights that improve campaign performance, user acquisition, and overall marketing efficiency.
• Support business integration and M&A projects by assessing marketing data ecosystems, consolidating reporting structures, aligning KPIs, and ensuring smooth data integration across organizations.
• Design, develop, and maintain scalable data models, ELT pipelines, and marketing datasets within modern cloud data platforms.
• Build intuitive dashboards and reporting solutions that provide clear visibility into marketing performance and business outcomes.
• Partner closely with marketing, product, engineering, and analytics teams to translate business challenges into scalable analytical solutions and actionable recommendations.
• Lead cross-functional analytics projects from planning through delivery, managing stakeholder communication, timelines, and project risks.
• Utilize AI tools and automation to improve data preparation, analysis, reporting, and insight generation while continuously enhancing analytical workflows.

• 5+ years of experience in marketing analytics, preferably within digital businesses, online marketplaces, or other data-driven environments.
• Proven experience supporting complex data integration, organizational transformation, or mergers and acquisitions involving KPI alignment, reporting consolidation, and stakeholder collaboration.
• Strong SQL expertise and hands-on experience building ELT pipelines using tools such as Airflow, dbt, or similar technologies.
• Experience working with cloud-based data platforms including BigQuery, Snowflake, Redshift, or equivalent solutions.
• Proficiency with business intelligence and data visualization tools such as Tableau, Power BI, Amazon QuickSight, or similar platforms.
• Solid understanding of Google Analytics, mobile measurement platforms, digital advertising ecosystems, and marketing attribution.
• Demonstrated ability to lead cross-functional analytics initiatives and communicate effectively with technical and business stakeholders.
• Interest in applying AI tools to enhance analytics workflows and improve the quality and efficiency of data-driven decision-making.
• Excellent written and verbal English communication skills.
• Availability to collaborate with international teams during Toronto (EST/EDT) working hours.
• Experience with attribution models, Google Search Console, Google Tag Manager, Amazon QuickSight, or mobile measurement platforms is considered an advantage.

• Fully remote work environment.
• Opportunity to work on large-scale, high-impact marketing analytics projects.
• International collaboration with cross-functional and distributed teams.
• Exposure to modern cloud data platforms, AI-powered analytics, and advanced marketing technologies.
• Career growth opportunities through leadership responsibilities and strategic initiatives.
• Dynamic, collaborative environment focused on innovation, continuous learning, and data-driven decision-making.