• Own the enterprise data architecture for the ECC → S/4HANA transition, defining principles, reference architectures, and guardrails for data domains (Finance, Supply Chain, Order‑to‑Cash, Procure‑to‑Pay, etc.). • Design the bridge reporting strategy that harmonizes ECC and S/4HANA datasets to produce consistent KPI definitions and cross‑system analytics (e.g., consolidated financials, inventory, order fulfillment), including semantic layers and data virtualization/replication as appropriate. • Model canonical and system‑specific data (conceptual, logical, physical) and establish golden sources, conformed dimensions, data standards, and naming/versioning conventions. • Define integration patterns (e.g., SLT/ODP/CDC, APIs, files, events) between SAP and the analytical stack, balancing latency, cost, reliability, and data quality. • Enable analytics & planning in SAP Analytics Cloud (SAC)—curate models, measures, and calculations; design security and data‑access patterns; guide dashboard/story design standards. • Oversee ETL/ELT pipelines using SAP BusinessObjects Data Services (BODS) and modern orchestration patterns; define error handling, lineage, and observability. • Create and maintain architecture artifacts (capability maps, value streams, domain models, roadmaps, standards) aligned to TOGAF ADM phases A–D and communicate them to technical and business stakeholders. • Coach delivery teams and provide architectural reviews to ensure solutions conform to strategy while meeting near‑term milestones during the phased migration.

• This candidate will be responsible for contributing to the Global Build of a Greenfield S4 implementation with a focus on data cleansing and data migration. • Responsibilities will include identifying prework activity which can and should be performed in our existing ECC environments, as well as managing the overall process of data migration to the new S/4 System. • The individual will leverage a strong technical background to troubleshoot complex issues and make recommendations for strategic changes to our landscape to improve the reliability and accuracy of existing solutions. • This position will require collaboration with a cross functional Digital Technology and Business team to develop and execute DT solutions in the data domain. • Identify data cleansing opportunities pre-migration. • Identify data migration objects needed to transition to S/4. • Oversee mapping of ECC to S/4. • Lead data validation effort as part of Mock and Go-live cutover.

• Design multimodal, multitask datasets that teach world models new capabilities — deciding what data to collect, generate, or curate and measuring its effect on model behavior • Run controlled training experiments to understand how data composition drives model performance across tasks and domains • Build and operate large-scale pipelines for synthetic data generation, filtering, and quality control • Define evaluations and benchmarks that measure whether our models are actually improving at the things that matter • Partner with product and creative teams to translate target behaviors and capabilities into concrete data strategies

• Own the cross-platform reference architecture for the Modern Data Platform across Databricks, Snowflake, and Fabric — and evolve it as platforms and partners change • Serve as the engagement-embedded tech lead on the active engagement: architecture, design reviews, and hands-on build on the hardest parts • Lead technical discovery with prospective health system partners — assess source environments (Epic Clarity/Caboodle, Cogito on Cloud, Bulk FHIR, flat-file SFTP) and design a defensible target state • Lead and develop a team of platform-specialist Senior Data Engineers and a Cloud/Platform Engineer; set the technical bar • Review and approve all engineering deliverables — IaC, ingestion patterns, data sharing topology, security controls • Partner with the Engagement Manager and Field CDO to scope SOWs, defend timelines, and surface technical risk before it becomes schedule risk • Coordinate technical handoffs to the QH Platform team via Delta Sharing / Reader Account so AI workflows can be deployed against the modernized foundation • Maintain the technical engagement playbook and a library of accelerators so each engagement starts further along than the last • Carry the technical narrative in pre-sales: present to CTOs, CDOs, and enterprise architects; convert technical credibility into signed work