Principal Solutions Architect

VizientIrving, TX
21h

About The Position

In this role, you will serve as a Principal Enterprise Solutions Architect, driving the architecture and development of large-scale digital platforms that support Vizient’s data and analytics needs. You will champion platform thinking, design thinking, and innovative architectural practices while partnering closely with Product, Engineering, Data Science, and Business leaders. This role blends deep technical expertise with strategic influence, enabling scalable, secure, and AI-driven solutions that deliver long-term value for Vizient and its members.

Requirements

  • High School diploma required; Bachelor’s degree in Computer Science, Information Systems, or a related field preferred (Master’s degree preferred).
  • 10 or more years of experience in architecture roles such as Enterprise Architect, Principal Solutions Architect, or equivalent.
  • Broad experience with large-scale database and data warehousing technologies such as Databricks or Snowflake, along with ETL, analytics, and cloud platforms.
  • Deep, hands-on experience with Databricks and Lakehouse architectures, including Delta Lake, Spark, and Unity Catalog.
  • Strong background in data engineering and analytics architecture, including medallion patterns and batch and streaming pipelines.
  • Experience integrating multiple data domains into cohesive, governed data products.
  • Expertise with cloud-native data platforms, preferably Microsoft Azure (AWS or GCP acceptable).
  • Strong understanding of data governance, security, lineage, and data quality, particularly in regulated environments.
  • Proven ability to influence across teams without direct authority and translate business needs into scalable architectural solutions.
  • Experience in healthcare or adjacent regulated domains such as clinical, claims, supply chain, or operations.
  • Hands-on experience designing semantic layers, metrics stores, or data product operating models.
  • Experience defining cross-domain KPIs, performance frameworks, or outcome-based analytics.
  • Strong background designing and implementing Generative AI and ML platforms at scale.
  • Knowledge of enterprise architecture frameworks such as TOGAF (certification preferred).
  • Exceptional visualization and storytelling skills for both technical and executive audiences.

Responsibilities

  • Lead end-to-end solution architecture for complex, cross-domain analytical products spanning clinical, spend, and operational data.
  • Define and drive technical strategy for enterprise data and analytics platforms, aligning architectural decisions with business and organizational goals.
  • Develop high-level architectural blueprints and provide guidance on modern data stacks, including cloud data warehouses and AI/ML systems, with a strong focus on Databricks (Lakehouse, Delta Lake, Unity Catalog).
  • Analyze complex business problems by conducting research and assessments to identify opportunities and recommend actionable, scalable solutions.
  • Design robust data pipelines, ETL/ELT processes, and conceptual, logical, and physical data models to support analytical products.
  • Lead proofs of concept (POCs), evaluate technology vendors, and oversee implementation of complex, scalable data solutions.
  • Establish architectural patterns for data products, semantic layers, domain models, and cross-domain analytics.
  • Ensure architectures meet enterprise standards for scalability, performance, reliability, security, governance, data quality, and observability.
  • Drive adoption of AI/ML and Generative AI capabilities, including architectures leveraging RAG, embeddings, agents, and LLM orchestration.
  • Partner with Data Science and Engineering teams to operationalize ML and GenAI solutions using production-grade patterns.
  • Act as a trusted architectural advisor to Product, Engineering, Platform, and Business leaders, influencing roadmaps and investment decisions.
  • Balance strategic architecture with delivery-focused execution, enabling teams to move quickly without compromising long-term sustainability.
  • Produce clear architecture diagrams and technical documentation to communicate complex concepts to technical and executive stakeholders.
  • Support enterprise decision-making by articulating architectural trade-offs, risks, and long-term implications.
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