• Partner closely with business stakeholders to elicit, challenge, and document requirements • Translate business needs into crisp functional and non-functional specifications • Work hand-in-hand with developers and data engineers throughout the full delivery lifecycle • Use Databricks to investigate business problems, validate hypotheses, and surface evidence-based recommendations • Plan and execute User Acceptance Testing (UAT) across all relevant deliverables • Continuously look for process improvements

• Structure and sustain the quality of master data (materials, business partners, assets, installation locations, and services) • Perform initial diagnostics and transition to continuous operation, executing data cleansing • Support master data registration workflows and monitor data quality • Establish quality baselines by domain (duplicates, completeness, validation) • Map the AS-IS master data lifecycle (creation, change, extension, blocking) • Support the design of TO-BE workflows and the definition of technical standards (taxonomy, match/merge rules) • Execute analyses for the data cleanup plan and build monitoring KPIs • Operate and evolve deployed master data workflows • Support the implementation of MDM solutions

• Partner with internal and external stakeholders to identify business challenges and develop analytical solutions to drive decision making • Lead and interpret data and communicate findings through effective storytelling • Contribute to the development of reusable data assets • Define, document and maintain key business metrics and reporting standards • Troubleshoot issues with existing and new data products and integrations • Mentor peers on both technical and non-technical aspects of analytical work • Create and maintain documentation for dashboards, data models, reporting assets and analytical processes • Communicate complex analytical findings into clear recommendations for technical and non-technical audiences • Support continuous improvement initiatives across the organization • Other duties as assigned

• Partner with Finance leadership to design, implement, and scale a financial analytics framework that enhances forecasting and business performance. • Build advanced data models to evaluate financial and operational performance, enabling deeper insight into revenue, margins, and key drivers. • Translate complex financial data into clear, actionable insights that support executives, BU leaders, and operational teams. • Identify opportunities to embed predictive and diagnostic analytics into financial decision-making. • Develop and maintain dashboards and reporting tools that provide timely, accurate, and relevant information to stakeholders. • Standardize financial reporting metrics, hierarchies and master data definitions, ensuring consistency across business units and corporate functions. • Leverage visualization tools (e.g., Power BI, Tableau, Oracle Analytics, or similar) to create intuitive, data-driven storytelling for executive audiences. • Work closely with business unit finance teams, Global Sales, and Corporate FP&A to ensure alignment on financial data and insights. • Partner with IT and data engineering teams to improve data infrastructure, data quality, and governance for financial analytics. • Support the adoption of data-driven decision-making across Finance by coaching and mentoring colleagues in analytics best practices. • Evaluate and introduce leading practices in financial analytics, modeling, and visualization. • Recommend enhancements to forecasting and planning processes using analytics-driven approaches. • Drive automation and efficiency in data preparation and reporting workflows.