Overview:
As an Applied AI Health Data Architect at PwC, you shape data architecture solutions for health services provider clients by uniting data engineering, analytics, and AI across cloud environments. You lead large modernization initiatives, setting strategic direction and guiding multi-team delivery through complex priorities. You design cloud-native data platforms and advocate data governance and AI-ready architecture. This role combines technical leadership with client advisory to drive impactful health data modernization. Compensation / Benefits medical, dental, vision 401k holiday pay vacation personal and family sick leave bonus eligibility
Responsibilities:
Lead applied AI and health data architecture initiatives for provider environments, translating business goals into scalable data solutions Design cloud-native data platforms, pipelines, and integration patterns across AWS, Azure, Databricks, and Snowflake Develop data models, warehouse structures, and transformation logic to support analytics, AI workloads, and reporting Guide data modernization efforts migrating legacy systems to modern architectures with improved performance, security, and usability Oversee data quality, governance, and anonymization practices across sensitive health data domains Apply data engineering methods to tune pipelines, optimize queries, and enhance DB and warehouse performance Advise client stakeholders on data strategy, architecture decisions, and AI-ready platform design Lead delivery planning, issue resolution, and technical coordination across multiple workstreams Coach practitioners on data engineering platforms, digital tooling, and AI-enabled solution delivery Present solution options, tradeoffs, and implementation paths aligned with modernization priorities
Key requirements:
Bachelor's degree 7+ years of experience Demonstrated data architecture leadership for healthcare provider modernization Experience with cloud data platforms (AWS, Azure, Databricks, Snowflake) AI fluency applied to data engineering and architecture decisions Ability to translate client needs into scalable modernization roadmaps Experience leading complex, multi-team delivery leadership stakeholder management clear communication cloud data platforms (AWS, Azure, Databricks, Snowflake) data modeling and warehouse design ETL/ELT and data pipelines
