• Scope difficult reporting questions and clarify the core business decisions the resulting reports must support • Audit and deconstruct complex customer marketing reports across legacy BI tools • Investigate data sources, identity resolution logic, metric definitions, and audience behavior to ensure accuracy • Train non-technical marketers on how to use AI effectively • Explain your analytical findings in a clear, actionable way for business decisions • Design, build, and tune the semantic context layer and document assumptions

• Develop, maintain, and automate complaint analytics dashboards, reports, and statistical trend analyses to monitor quality performance, identify emerging signals, and support Quality Management Reviews, CAPA activities, and business decision-making. • Ensure the integrity, accuracy, and governance of complaint and quality system data through validation, reconciliation, audit trail management, and continuous improvement of reporting processes. • Provide data-driven support for complaint investigations, root cause analysis, risk management activities, and CAPA effectiveness evaluations to strengthen product quality and patient safety outcomes. • Collaborate with Quality Assurance, Regulatory Affairs, Scientific Application Support, Product Development, Manufacturing, Process Engineering, and other cross-functional stakeholders to identify trends and drive continuous improvement initiatives. • Support regulatory compliance, internal and external audits, and inspections through accurate reporting, analysis, documentation, and application of quality system requirements.

• Design, develop, and maintain advanced Power BI data models, dashboards, and reports for integrated business analytics • Build and optimize semantic models with a focus on performance tuning and efficient DAX implementation • Develop data collection tools using Power Apps and workflow automations using Power Automate and Python • Design and implement Python-based data automation pipelines • Perform data extraction, transformation, and loading (ETL) from multiple sources including SAP, SharePoint, and other enterprise systems or cloud storage services • Develop and deliver integrated analytics solutions leveraging prior team frameworks and reusable components • Collaborate with cross-functional stakeholders to translate business requirements into analytical solutions • Monitor and sustain existing solutions, troubleshoot issues, and enhance performance and usability (approx. 30% of role) • Lead or collaborate on new development initiatives with short project cycles (1–2 months, approx. 70% of role) • Ensure data quality, integrity, and proper data governance across solutions • Maintain clear documentation of datasets, models, and workflows

• Design and develop data integrations to deliver Enterprise BI Data Marts and BI Semantic Data Layer(s) • Develop modern data engineering pipelines leveraging AI assisted capabilities, such as Databricks GenAI features • Lead multiple projects, provide technical guidance, and support other team members within the DAS organization • Improve data processes, technology infrastructure, and reporting and analytical services