Provide the tools necessary to deliver cutting-edge health care and groundbreaking research. As part of our Information Technology team, you’ll ensure that our medical professionals have access to the latest breakthroughs in technology, and you’ll play a key role in protecting our global patient community.
The Senior Data Architect will play a pivotal role in shaping the future of UCLA Health’s enterprise data ecosystem as we transition to a modern, cloud-native platform built on Azure Databricks and Microsoft Fabric. This leader will define the architectural vision, establish enterprise standards, and guide the design of scalable, secure, and AI‑ready data systems that power analytics, machine learning, and emerging generative AI capabilities across the organization.
In this role, the focus extends far beyond hands‑on implementation. The Senior Data Architect will drive enterprise‑level decision‑making related to data modeling, engineering best practices, governance and compliance integration, and long‑term platform sustainability. Partnering closely with Product Data Engineering, Analytics, Data Science, and Research, this individual ensures that data is reliable, well‑governed, and effortlessly consumable for both traditional analytics and advanced AI workloads.
Success in this position requires strong architectural judgment and the ability to navigate the complexities of a large healthcare enterprise—balancing performance, cost, security, compliance, and usability. As UCLA Health accelerates its adoption of AI, this architect will ensure foundational data structures support feature reuse, semantic consistency, trusted access patterns, and scalable integration with AI and LLM‑driven systems.
This is a unique opportunity to influence the data and AI strategy of one of the nation’s leading academic health systems. Your work will directly contribute to improving patient care, advancing research, and enhancing operational efficiency across UCLA Health.
This flexible hybrid role allows for a blend of remote and on-site work, requiring presence on-site at least 10% of the time, and as needed by operational requirements. Please note, travel to the “home office” location is not reimbursed. Each employee will complete a FlexWork Agreement with their manager to outline expectations and ensure mutual understanding. These arrangements are periodically reviewed and may be adjusted or terminated as necessary.
Salary offers are based on a variety of factors including qualifications, experience, and internal equity. The full salary range for this position is $128,500 – $298,100 annually. The University anticipates offering a salary between the minimum and below the midpoint of this range.
This is a three year contract role. Contracts may convert to a Career position.
- · 7+ years of experience in data architecture or data engineering with demonstrated ownership of large-scale data systems.
- · Strong experience designing enterprise data architectures for analytics and advanced analytical workloads, not just individual pipelines.
- · Deep understanding of data modeling, data warehousing, and Lakehouse architectures, including trade-offs between performance, cost, and governance.
- · Proficiency in SQL and at least one general-purpose programming language such as Python or Java, with strong grasp of distributed data processing concepts.
- · Hands-on experience with Spark-based platforms or equivalent distributed processing technologies.
- · Experience working with cloud data platforms on Azure, AWS, or GCP, with the ability to adapt architectural patterns across cloud ecosystems.
- · Solid understanding of how data architectures support machine learning and AI, including feature engineering, data versioning, and lifecycle management.
- · Familiarity with feature stores, semantic layers, knowledge graphs, or metadata-driven architectures used to enable analytics and AI.
- · Exposure to LLM-enabled or AI-driven data use cases (e.g., RAG-style architectures or document processing frameworks) is a plus.
- · Strong communication skills, with the ability to influence technical direction and clearly explain architectural decisions to engineering teams and leadership.
- Bachelor’s degree in computer science, Engineering, or a related field from an accredited institution
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