Data AI Architect at MGMA-ACMPE Englewood
Job in
Englewood, Arapahoe County, Colorado, 80151, USA
Listed on 2026-07-08
Listing for:
Shell Lubricants Hub Hamburg
Full Time
position Listed on 2026-07-08
Job specializations:
-
IT/Tech
Data Engineering, Cloud Computing: Infrastructure & Operations, Data Analyst
Job Description & How to Apply Below
Job Description
Data AI Architect, MGMA-ACMPE. Englewood, CO. The Medical Group Management Association (MGMA) is seeking a Data AI Architect to join our Denver/hybrid team. This role designs, implements, and optimizes data & AI solutions to support the organization’s strategic goals and operational needs.
Responsibilities- Design data and AI/ML architectures to implement business strategies and roadmaps.
- Create and maintain data models that support business requirements.
- Collaborate with Data Governance and Security Leads to oversee and enhance data governance and security protocols to protect data integrity and confidentiality.
- Work closely with cross‑functional teams to understand data needs and ensure alignment with architectural standards.
- Evaluate and optimize data storage and retrieval systems to improve efficiency and performance.
- Establish and enforce data standards and best practices to ensure consistency and quality across the organization.
- Research and recommend new technologies and methodologies that can enhance data architecture and address evolving business needs.
- Other duties as required and necessary to ensure the success of the organization.
- None
- Ability to consistently promote, support, work, and act in a manner in support of MGMA’s mission, vision, and values/behaviors.
- Expertise in creating conceptual, logical, and physical data models that accurately represent business requirements and facilitate efficient data management and AI practices, and patterns.
- Expertise in modern data architectures.
- Strong knowledge of database management systems; data warehousing, lakehouse, and data lake solutions; and data integration and wrangling tools and approaches.
- Deep expertise in SQL, Python, R, and Bash.
- Strong expertise in machine learning algorithms and approaches.
- Practical experience with AI tools.
- Knowledge of MLOps best practices.
- Expertise in Power BI, Tableau, or similar applications for data visualization.
- Ability to implement and maintain data governance frameworks and security protocols to ensure data integrity, compliance, and protection.
- Awareness of current trends and emerging technologies that support organizational data maturity.
- Bachelor’s degree in computer science, data science, or relevant discipline, or equivalent skills developed through related work experience
- MS in data science or related field preferred
- Experience in designing and implementing modern data architectures on cloud platforms, preferably on Azure
- Experience developing data architecture, strategy, and roadmaps
- Define data models, data flow diagrams, and architecture blueprints to guide the implementation of data solutions.
- Create and maintain an enterprise architecture strategy that aligns with the organization's goals for managing and leveraging internal, product, and customer data.
- Architectural Design and Planning
- Lead proof‑of‑concept initiatives to validate technology choices.
- Design and document architecture blueprints that outline the structure and integration of data systems, applications, and technology infrastructure to support data management.
- Present complex ideas and architectural designs to various stakeholders, including business stakeholders, engineers, and executives.
- Familiarity with Agile/Scrum methodologies.
- Technology Evaluation and Selection
- Identify, evaluate, and recommend technology solutions and platforms that enhance the organization's ability to capture, store, analyze, visualize, gain insight from, and utilize data effectively.
- Routinely assess data storage solutions, ensuring alignment with security, compliance, and performance requirements.
- Stay informed about emerging technologies and industry trends related to data management, data science and AI, and customer experience, and identify opportunities to innovate and enhance the enterprise architecture.
- Integration and Interoperability
- Design scalable data integration frameworks that enable seamless data flow across diverse systems and platforms.
- Data Governance and Security
- Integrate data governance tools into the data architecture, including managing ingestion processes, configuring…
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