Darum lohnt es sich
Responsibilities
• Lead and mentor teams responsible for reporting modernization and AI/ML-enabled process transformation
• Set strategic direction and execution standards for reporting, analytics, and automation initiatives
• Develop and implement transformation strategies aligned with enterprise goals and business priorities
• Ensure teams are appropriately skilled, trained, and enabled to deliver modern reporting and AI/ML solutions
• Drive standardization, simplification, and automation of reporting processes across functions
• Establish scalable reporting and analytics frameworks that improve transparency, speed, and decision quality
• Partner with Finance and business stakeholders to define KPI frameworks and performance measurement models
• Identify and deliver AI/ML use cases that improve efficiency, accuracy, and insight generation
• Oversee multiple transformation initiatives and workstreams, balancing priorities and dependencies
• Communicate progress, insights, and value delivered through reporting and AI/ML initiatives
Requirements
• Minimum 10 years of hands‑on experience in data engineering
• Minimum 4 years of relevant work experience within a large, complex organization
• Minimum 1 year of experience delivering Generative AI applications into production
• Strong understanding of reporting, analytics, and data‑driven decision‑making within Finance or enterprise functions
• Familiarity with modern data platforms, reporting tools, and analytics ecosystems
• Related Cloud certification (e.g.
GCP, AWS, Azure)
• Hands‑on experience on BigQuery and/or Databricks is highly preferred
• Bachelor’s degree in Finance, Business Administration, Data Analytics, Information Technology, or related field; equivalent years of related professional work experience may substitute
• Advanced degree or certifications in analytics, data science, or transformation disciplines preferred