• 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

• Work forward-deployed inside the customer's environment • Own platform-specific architecture and build for your stack during active engagements • Design and implement ingestion from EHR and source systems (Epic Clarity / Caboodle, FHIR, ERP, scheduling, claims) into a medallion lakehouse • Build and harden change-data-capture, transformation, and orchestration pipelines that meet engagement timelines • Configure governance, access control, and the data-sharing pattern that hands clean, AI-ready data to QH's platform • Sustain production environments handed off from prior engagements • Support pre-sales technical discovery and source-data assessment • Ensure every environment meets handoff criteria for the Client Integration team • Cross-train on the other two platforms to keep the team flexible across single- and multi-engagement states