AI & Data Analytics Architect

TTX•Charlotte, NC

About The Position

The AI & Data Analytics Architect role is responsible for designing and guiding the implementation of enterprise-wide AI, data analytics, and data architecture platforms and integrated solutions, primarily in the cloud. As a member of the Solutions Architecture team, this role bridges business strategy and technical execution by translating organizational goals into secure, governed, and scalable data and AI architecture. This role requires producing architectural designs for multiple concurrent efforts, as well as providing implementation teams with guidance on best practices, architectural trade-offs, cost estimates, and technology decisions in collaboration with stakeholders and IT leadership.

Requirements

Bachelor’s degree required.
10+ years of professional experience with demonstrated progressive responsibility in database modeling, development, deployment, analytics, and related technologies.
4+ years of professional experience with cloud-based data and analytics architectures and implementations preferably Azure.
1–2 years of professional experience implementing AI solutions.
Ability to design, plan, and lead long-term, high-level technological initiatives.
Exceptional communication skills to bridge the gap between technical teams and non-technical stakeholders.
Strong proficiency in AI/ML principles, MLOps, data engineering, and cloud platforms, particularly Azure and Oracle.
Demonstrated deep understanding of the Azure data stack, data handling, ETL processes, and analytics.
Demonstrated expertise in Azure data and analytics services.
Demonstrated experience with data security and privacy protection measures.
Proactively stay informed on new technologies and practices related to AI and data analytics.
Ability to quickly and effectively evaluate and experiment with new technologies, translate that knowledge into information for others to learn quickly, and make recommendations based on the information at hand.
Ability to quickly design solutions that meet requirements and provide business value.
Results-oriented individual with strong problem-solving, influencing, consensus-building, and negotiating skills.
Knowledge of on-premises, cloud, and hybrid data practices to deliver innovative solutions.
Knowledge of the following tools: M365 Copilot, Copilot Studio, Microsoft Foundry, GitHub Copilot Azure Machine Learning, Microsoft Fabric, Power BI, Oracle Fusion Analytics, Microsoft Purview. Azure Synapse Analytics, Azure Data Lake Storage (ADLS) Gen2. Azure SQL Database, Azure SQL Managed Instance, SQL Server, and SSIS
Demonstrated ability to work independently, follow direction, and take initiative.
Demonstrated strong communication and interpersonal skills.
Demonstrated ability to collaborate with cross-functional teams and solve complex problems.

Nice To Haves

Preferred knowledge of the following tools: Incorta, Azure Cosmos DB, Azure AI Search, WhereScape

Responsibilities

Architect and guide the implementation of enterprise-wide artificial intelligence and data analytics tools and solutions using approved platforms, tools, and services.
Develop end-to-end architecture solutions, including operational and analytical systems, ensuring alignment with enterprise policies and standards for data governance and security.
Design end-to-end data pipelines, storage systems, and analytics architectures (batch or real time) using Azure services.
Design solutions that integrate AI and ML models into data solutions, leveraging Azure Machine Learning, Microsoft Foundry, approved LLM services, and cognitive services for predictive and generative AI use cases.
Provide solutions that incorporate data security, compliance, and governance frameworks to ensure data reliability, quality, and security.
Help define enterprise governance and AgentOps patterns for AI and agent solutions, integrating security, Responsible AI guardrails, evaluation, observability, cost controls, and lifecycle management into repeatable, production-ready practices.
Design data solutions using modern data platform capabilities (e.g. Lakehouse, warehouse, semantic models) leveraging primarily Azure services for unified data and AI governance while balancing existing legacy data warehouse architectures.
Contribute to the development and adoption of enterprise AI and data architecture patterns, reusable solution templates, and technical standards in collaboration with the AI CoE.
Design solutions that leverage cloud services for AI tasks, ensuring security, compliance, and cost efficiency.
Collaborate with senior leaders, users, enterprise architects, solution architects, data analytics team members, software engineers, and other stakeholders to understand requirements; provide effective, timely solutions; and mentor others as needed.
Work with users and vendors to conduct evaluations of various technologies in support of solution design.
Evaluate new tooling and solutions to further the organization's AI and data strategy, identifying opportunities to leverage AI to achieve business goals, and developing a roadmap for implementing these solutions.
Partner with the AI CoE, Enterprise Architecture, and delivery teams to ensure AI and analytics solutions align with established governance processes and enterprise technology strategy.
Maintain awareness of emerging products, features, and industry trends related to AI, machine learning, and analytics platforms. Support technology lifecycle planning and maintain the CMDB as needed.