Data & Analytics Lead Architech

• The Data & Analytics Architect is responsible for defining and managing the enterprise data architecture that enables scalable analytics, reporting, and AI across the organization. This role ensures our data ecosystem is integrated, governed, and aligned to business priorities, while supporting a federated (hub-and-spoke) operating model. This person partners closely with IT, clinical, operational, and finance leaders to translate business needs into a modern, sustainable data platform.

o # Proven experience as a Data Architect or similar role with extensive knowledge of NoSQL, SQL, Hadoop, Spark, Oracle, Microsoft SQL Server, and Microsoft Fabric Data Lake # Experience in healthcare strongly preferred (EHR, claims, revenue cycle, etc.). # Strong expertise in *data modeling, database design, ETL processes, and data warehouse architecture. # Direct experience working with cloud platforms such as AWS and Azure for deploying scalable data solutions. # Experience working within Agile development environments with a focus on analytics projects involving large datasets (Big Data) and distributed computing frameworks like Hadoop., # Bachelor’s degree in computer science, data science, engineering, or related field., o Familiarity with programming languages including Java, Python, and scripting with Bash (Unix shell) o Knowledge of linked data concepts and experience integrating diverse datasets for advanced analytics applications is a plus. o This position offers an engaging environment where innovative thinking is valued, and the successful candidate will play a pivotal role in shaping our organization’s data strategy through advanced architecture solutions. o Familiarity with governance frameworks and federated data models. o Ability to translate business strategy into technical architecture. o Ability to guide solution design and architecture to meet business needs. o Strong stakeholder engagement (can work across clinical, operational, and IT teams). o Systems thinker-can connect data, workflows, and outcomes. o Pragmatic decision-maker (not over-engineering solutions).

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