Data Architect

Must-Haves:

• Education: Bachelor’s degree.

• Experience: Minimum of 2 years.

Must-Haves:

• 2 years of data-related experience (data modeling, data analysis, database development)
• Proficiency with data modeling principles and performance considerations (e.g., star schemas, snowflake schemas, wide tables, medallion design)
• Strong understanding of relational databases, data warehousing concepts, and SQL
• Experience with DevOps tools, particularly GIT
• Ability to collaborate with senior data architects to design and refine data models
• Experience working closely with data engineers, analysts, and data scientists to understand project requirements and data workflows
• Basic experience with business intelligence tools such as Microsoft Power BI

Plusses:

• Relevant data modeling or cloud certifications (e.g., Microsoft Azure, Snowflake)
• Clinical or healthcare-related credentials (e.g., RN/BSN, EMT)
• Familiarity with healthcare quality measures (e.g., CMS, Leapfrog, US News)
• Strong presentation skills

Day-to-Day: In this role, you will support the Clinical Analytics and Performance Improvement teams by designing and maintaining data structures like data warehouses, data lakes, and lakehouse architectures. You will learn and apply best practices in data modeling, including star schemas, snowflake schemas, and wide tables, while exploring advanced techniques like medallion layering. You will collaborate closely with senior team members, data engineers, analysts, and data scientists to understand project requirements and data workflows. Daily stand-ups with the team will be part of your routine. Your responsibilities include supporting corporate analytics teams, working with clinical stakeholders, designing tables using SQL and DevOps (GIT), and collaborating with engineers using ADF Azure. Analysts will work with the Snowflake environment to pull data and perform analyses.

You will interact with internal teams, external vendors, end users, and security and AI governance committees to ensure compliance and improve workflows. The ideal candidate is eager to learn, collaborates well, and translates requirements into practical data solutions.