10.11.2025 aktualisiert
TÜ
Premiumkunde
100 % verfügbarData & Analytics Consultant
Berlin, Deutschland
Weltweit
Bachelor of Science in Business Information TechnologySkills
Data AnalysisBusiness IntelligenceBusiness AnalysisDatenverarbeitungData ArchitectureDatenmanagementDatenqualitätData VaultData WarehousingE-CommercePythonPower BiRequirements EngineeringPL/SQLSQLStakeholder ManagementSnowflakeData Build Tool (dbt)Databricks
Business-focused Data & Analytics Professional with 7 years of experience bridging business requirements and technical implementation in enterprise Business Intelligence and data warehouse environments. Specialized in requirements engineering, stakeholder management, and translating complex business needs into actionable data solutions. Deep expertise in modern data architectures including Data Mesh and Data Vault 2.0, combined with strong analytical capabilities and advanced SQL proficiency for complex data analysis and problem-solving. Proven track record in leading cross-functional teams and delivering analytics solutions that drive strategic business decisions across insurance, real estate, and e-commerce industries.
Sprachen
DeutschMutterspracheEnglischverhandlungssicherTürkischverhandlungssicher
Projekthistorie
• Led domain-specific BI requirements and roadmap development as Data Owner within the insurance company's Data Mesh transformation initiative
• Developed complex SQL queries and data models on Azure Databricks to analyze insurance sales performance, policy conversion rates, and customer acquisition metrics
• Built interactive Power BI dashboards and reports that delivered actionable insights to executive leadership for strategic decision-making
• Managed agile delivery processes and created comprehensive documentation that facilitated cross domain collaboration within the insurance organization
• Orchestrated the seamless migration from Adobe Campaign to Salesforce Marketing Cloud, ensuring data integrity and minimal business disruption
• Mentored junior analysts, establishing best practices that improved team delivery quality and velocity
• Developed complex SQL queries and data models on Azure Databricks to analyze insurance sales performance, policy conversion rates, and customer acquisition metrics
• Built interactive Power BI dashboards and reports that delivered actionable insights to executive leadership for strategic decision-making
• Managed agile delivery processes and created comprehensive documentation that facilitated cross domain collaboration within the insurance organization
• Orchestrated the seamless migration from Adobe Campaign to Salesforce Marketing Cloud, ensuring data integrity and minimal business disruption
• Mentored junior analysts, establishing best practices that improved team delivery quality and velocity
• Led requirements engineering for a cloud data warehouse implementation, translating business needs into technical specifications
• Developed implementation roadmap prioritizing high-impact deliverables that aligned with business objectives
• Ensured seamless integration of multiple data sources from the real estate portfolio while maintaining data quality standards
• Developed implementation roadmap prioritizing high-impact deliverables that aligned with business objectives
• Ensured seamless integration of multiple data sources from the real estate portfolio while maintaining data quality standards
• Architected and implemented a Data Vault 2.0 based data warehouse that improved data modeling flexibility and significantly reduced time-to-insight
• Developed ETL/ELT processes using PL/SQL and SQL that optimized data pipeline performance and enhanced processing efficiency
• Established automated data quality frameworks with monitoring capabilities that improved data integrity across systems
• Analyzed business requirements and translated them into technical specifications within Scrum processes
• Led quality assurance initiatives, creating comprehensive test cases and documentation that minimized post-deployment issues
• Developed ETL/ELT processes using PL/SQL and SQL that optimized data pipeline performance and enhanced processing efficiency
• Established automated data quality frameworks with monitoring capabilities that improved data integrity across systems
• Analyzed business requirements and translated them into technical specifications within Scrum processes
• Led quality assurance initiatives, creating comprehensive test cases and documentation that minimized post-deployment issues