EY - GDS Consulting - AIA - Agentic AI - Senior

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Career Family: AIA – AGENTIC AI ENGINEER   Technology - Cloud & Data Engineering – Senior Associate Agentic Data Engineer (Healthcare) The Opportunity Healthcare is rapidly adopting Artificial Intelligence to improve patient outcomes, operational efficiency, and member experiences. As AI moves from experimentation into production, organizations need trusted, scalable, and AI-ready data foundations that enable intelligent applications and agentic systems to deliver meaningful business value. Our Artificial Intelligence, Data and Engineering team helps healthcare organizations build modern cloud-based data platforms that power analytics, machine learning, generative AI, and emerging agentic AI capabilities. As an Agentic Data Engineer, you will work alongside healthcare, cloud, and AI specialists to design, build, and support data solutions that enable secure, governed, and scalable AI adoption within payer and provider organizations. This role provides an opportunity to gain hands-on experience with healthcare data, cloud technologies, interoperability standards, and AI-enabled data platforms while working with leading healthcare clients.   Your Key Responsibilities You will contribute to the implementation of healthcare data platforms and AI-ready data solutions, helping clients modernize their data ecosystems and accelerate AI adoption.   Responsibilities include:

Develop and maintain cloud-based data pipelines to ingest, transform, validate, and process healthcare data from sources such as EHR/EMR systems, claims platforms, operational systems, and external healthcare data providers. Support the development of AI-ready healthcare data products, including curated datasets, semantic layers, feature stores, and reusable healthcare data assets. Participate in healthcare interoperability initiatives involving standards such as FHIR, HL7, CDA/CCDA, APIs, and healthcare integration platforms. Assist in building data foundations that support AI and Generative AI use cases, including document processing, retrieval systems, vector databases, knowledge repositories, and governed data access patterns. Implement data quality checks, monitoring, observability, lineage, and governance controls within healthcare data pipelines. Work with cross-functional teams including data engineers, AI engineers, architects, healthcare SMEs, and business stakeholders to deliver client solutions. Support cloud platform deployment activities using modern engineering practices such as CI/CD, Infrastructure as Code, and DataOps. Participate in technical workshops, requirement gathering sessions, testing activities, and production support initiatives. Contribute to reusable accelerators, templates, and best practices for healthcare data and AI implementations.

Skills and Attributes for Success To succeed in this role, you should have a strong foundation in data engineering, cloud technologies, and a passion for healthcare and AI innovation.   Key attributes include:

Understanding of modern data engineering concepts including ETL/ELT, data modeling, data warehousing, lakehouse architectures, and cloud-based analytics platforms. Ability to work with structured and unstructured healthcare data while ensuring data quality, privacy, and compliance requirements. Interest in AI, Generative AI, and emerging agentic AI technologies and their application in healthcare use cases. Strong analytical and problem-solving skills with attention to detail. Effective communication skills and ability to collaborate within cross-functional teams. Willingness to