We are seeking a Data Architect to design the structural backbone of a high-scale multi-modal healthcare data ecosystem. You will be responsible for architecting data environments that serve massive networks of hospitals ensuring that diverse data types—ranging from structured EHR records to unstructured genomic and imaging data—are seamlessly accessible to autonomous AI agents.

Our goal is to move beyond static data warehousing to create a dynamic "agent-ready" data fabric that supports real-time clinical evaluation at an enterprise scale.

• Multi-Modal Architecture: Lead the design and management of an enterprise data model that integrates complex domains including clinical EHR records high-throughput genomics (NGS) and cardiovascular imaging (Echo Cath ECG).

• Scale for Hospital Networks: Architect data solutions designed to scale across federated networks of hospitals ensuring multi-tenancy high availability and performance across hybrid cloud environments.

• Enable Agentic Workflows: Design data access patterns and metadata layers specifically optimized for AI agents allowing them to autonomously discover query and reason over structured and unstructured datasets.

• Schema & API Ownership: Author and maintain entity-relationship diagrams (ERDs) data dictionaries and API specifications across multiple technologies (Relational NoSQL Vector Databases).

• Data Quality & Traceability: Implement automated solutions to monitor data quality and lineage with strict traceability back to source systems ensuring "ground truth" for agentic evaluations.

• Technical Advocacy: Educate engineering and clinical teams on data modeling standards governance and best practices for maintaining data integrity in a HIPAA-regulated environment.

• Education: Bachelor’s Degree in Computer Science Health Informatics or a related field.

• Professional Experience: 7+ years in data architecture or enterprise modeling with significant experience in the healthcare or life sciences domain.

• Modeling Mastery: Expert-level knowledge of 3NF Dimensional (Star Schema) and Data Vault 2.0 modeling techniques.

• Advanced SQL & Python: Exceptional SQL skills for complex analytical environments and proficiency in Python for data profiling and debugging.

• Technology Strategy: Ability to articulate the trade-offs between RDBMS MPP and NoSQL technologies and experience implementing Master Data Management (MDM) solutions.

• Interoperability Standards: Deep familiarity with HL7 FHIR and Epic/Cerner data structures.

• Tools: Proficiency with modeling tools such as Erwin Vertabelo or Lucidchart.

• AI Data Engineering: Experience with Vector databases (e.g. Pinecone Weaviate or pgvector) or Graph databases to support RAG and agentic memory.

• Cloud Architecture: Hands-on experience with GCP (BigQuery Vertex AI) or AWS healthcare-native services.

• Specialized Clinical Data: Direct experience working with EHR OMOP DICOM genomic data models or longitudinal patient records.

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