• Design and build key features and architectural improvements end-to-end — from technical discovery and system design through implementation, testing, and production support. • Write production code daily in critical services, pipelines, and frameworks, using modern cloud-native patterns and technologies. • Provide mentorship to the other developers on your team through design reviews, pair programming, and code reviews. • Build deep expertise in the technology and architecture powering the Data Analytics Platform and use that knowledge to drive sound technical decisions. • Collaborate with Product and Engineering to disambiguate requirements, surface technical uncertainty, and clearly communicate trade-offs and risks. • Champion engineering excellence by keeping trunk/master green, stable, and deployable through strong CI/CD, testing, and operational practices. • Coordinate with DevOps/CloudOps teams to ensure your squad has the tooling, infrastructure, and support needed to ship confidently. • Own production reliability for the systems your squad manages, driving continuous improvement through post-mortems and root cause analysis. • Provide 24/7 production support for the systems your team manages, driving continuous improvement in this area through post-mortems and root cause analysis.

• Work closely with development teams and end clients to configure, maintain, and optimize digital analytics solutions across all digital properties • Translate business requirements into technical tracking solutions alongside Front-End developers • Analyze user behavior data to generate actionable insights • Ensure data consistency and quality across implementations • Integrate analytics platforms with advertising and social media channels • Coordinate and prioritize analytics-related tasks across multiple concurrent projects

• 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.