Senior Principal Data Architect

This position is incentive eligible.

Born from our Care Transformation and Innovation team, DT&I was created to expand HCA Healthcare’s digital and AI strategy. We’re building intelligent systems, enhancing workflows, and driving innovation across a nationwide network. If you’re ready to build technology that saves lives and improves care, your future starts here.

The Principal Data Architect
- Multi-Modal Ingestion & Intelligent Lakehouse Platforms (GCP) is a senior technical leadership role responsible for defining and delivering next-generation data architecture capabilities for HCA’s enterprise data ecosystem. This role focuses specifically on multi-modal ingestion frameworks and intelligent document management within a GCP-based Lakehouse architecture, optimized for cost efficiency, scalability, performance, and insight generation.

This individual will lead the design and evolution of platforms that ingest, process, store, govern, and serve structured, semi-structured, and unstructured data (documents, text, images, PDFs, audio/video metadata) using modern data engineering techniques, LLMs, and AI-assisted pipelines. The role requires deep expertise in GCP, Lakehouse patterns, and advanced data ingestion strategies, combined with the ability to translate business and clinical needs into durable, enterprise-grade architectures.

As a Principal Architect, this role sets technical direction across multiple teams, mentors senior engineers and architects, and acts as a key partner to Data Engineering, AI/ML, Security, and Governance organizations. The outcome is a secure, governed, and intelligent data platform that accelerates analytics, AI adoption, and operational insight across HCA.

• Strategic thinking and architectural leadership
• Deep technical expertise in cloud data platforms
• Strong problem-solving and systems design skills
• Ability to bridge business, clinical, and technical domains
• Clear written and verbal communication

This role will focus on setting technical direction on groups of applications and similar technologies as well as taking responsibility for the implementation of technically robust solutions encompassing all business, architecture, and technology constraints.

• Define and own enterprise-scale data architecture patterns for multi-modal ingestion and Lakehouse platforms on Google Cloud Platform.
• Architect and evolve document-centric and unstructured data pipelines that support ingestion, enrichment, embedding, indexing, storage, and retrieval at scale.
• Lead the design of intelligent ingestion frameworks leveraging LLMs and advanced techniques (e.g., semantic chunking, embeddings, metadata extraction, classification, and enrichment).
• Establish architectural standards for cost-optimized, high-throughput ingestion across batch, streaming, and event-driven workloads.
• Drive platform designs that support search, analytics, and downstream AI/ML use cases in partnership with the AI/ML organization.

• Architect and manage enterprise Lakehouse environments using technologies such as Big Query, Apache Iceberg, Delta Lake, and GCS.
• Ensure strong design around schema evolution, ACID compliance, partitioning strategies, metadata management, and lifecycle policies.
• Optimize storage and compute usage to balance performance and cost across large-scale document and data repositories.
• Design data models and access patterns that support both analytical and AI-driven workloads.

• Design and oversee ETL/ELT and ingestion pipelines using Dataflow, Dataproc, Pub/Sub, Cloud Run, GKE, and related services.
• Integrate AI/ML services into ingestion and processing pipelines for document understanding and content intelligence in partnership with that practice area.
• Partner with AI/ML teams to enable embedding generation, vector storage, and retrieval patterns aligned with enterprise governance standards.
• Ensure ingestion frameworks are resilient, observable, and designed for continuous evolution.