• Analyze and further develop the HR system architecture with a focus on SAP SuccessFactors • Design and implement integration scenarios between SAP HCM and SuccessFactors • Advise on best practices for modules such as Employee Central, Time Management, Recruiting, Onboarding and Payroll • Create technical concepts and interface designs (e.g., SAP BTP, middleware) • Participate in migration projects and go-live phases • Collaborate with project management, developers and business stakeholders • Pre-sales activities: participate in client workshops and presentations • Prepare solution proposals and support tendering processes • Demonstrate SuccessFactors functionality to prospective clients

• Research & understand both our products, SAP’s and our partners products in this space • Take inputs from Professional Services teams on what functionality we are missing or is sub-optimal in the solutions suites we used today • Prototype solutions on a branched codebase of our software • Liaise with partners on how we use & co-innovate with their technologies • Lobby & help push forwards our analytics platform that analyses systems (before we then go and transform them).

• Iterating with UX designers to transform use cases into UX/UI prototypes. • Breaking down release milestones into high-level execution plans. • Writing highly detailed troubleshooting articles that are the core of our Knowledge Base. • Defining the granular tasks needed by engineering to implement releases. • Reviewing and accepting engineering work, ensuring it meets all of your requirements.

• Design analytical models that represent how core business processes operate across Oak Street Health. • Translate complex operational systems into structured, reusable analytical frameworks that support measurement, forecasting, and decision making. • Build and maintain Power BI semantic models that expose consistent metrics and business definitions across the organization. • Investigate operational data sources to understand how the business actually functions and identify opportunities to improve measurement and transparency. • Partner with data engineering, analytics engineering, product, and operational teams to inform upstream data requirements needed to support robust analytical models. • Contribute to the development of analytics-ready datasets and semantic models that can support advanced analytics, machine learning, and AI-driven decision support. • Develop analytical artifacts including models, metric frameworks, and reports that help the organization monitor performance and identify opportunities for improvement.