Business Impact Coaches the team on operating to required operational excellence and proven practice standards across all engagement stages, activities, and tools of record (e.g., pipeline updates, consumption tracking, time tracking). Oversees the team in anticipating and managing business and technical risks for data and AI workloads — including data quality, data governance, model performance, cost, and Responsible AI considerations — applying governance principles to identify, communicate, and minimize risk. Leads the team in delivering solutions in line with company methodologies (e.g., value-based deliverables [VBDs], architecture design sessions, technical validation, training), ensuring proven patterns are followed so customers are operationally ready to run data and AI workloads in production. Coaches the team on guiding customers toward well-architected (secure, resilient, governed, AI-ready), cost- and performance-optimized data platforms and AI solutions that increase retention and expansion opportunities. Guides the team on articulating the value of Unified and partnering with account teams to build consumption plans aligned with the right Data & AI services. Leads feedback to the Unified Delivery team on Data & AI VBDs to refine and further develop content. Leverages change management proven practices (or engages the change management team) to help customers drive long-term organizational adoption of data and AI solutions, including data literacy and AI adoption. Drives the team on anticipating, identifying, escalating, and mitigating blockers — such as data readiness, platform limits, capacity and quota, security reviews, and skills gaps — to accelerate deployment, value realization, and consumption. Managers deliver success through empowerment and accountability by modeling, coaching, and caring. Enable success across boundaries. Leads the team in identifying gaps through delivery and connecting patterns across business and technology areas to drive improvements to products, intellectual property (IP), and practices that enable Data & AI solutions to scale across customers. Leads the team in contributing to and building reusable IP — reference architectures, accelerators, and solution patterns — especially where no IP exists yet (e.g., generative AI, AI agents, Copilot extensibility, RAG, and real-time intelligence scenarios). Uses market insights and demand signals to help leadership prioritize up-skilling and accreditations. Drives the team to role-model technical readiness — depth in Data & AI (data engineering, analytics, data science, MLOps/LLMOps, generative and agentic AI) and breadth across CSU priorities such as security, resilience, and AI. Ensures team members dedicate time to continuous learning and certification, monitoring progress and providing guidance where appropriate. Bachelor's Degree in Computer Science, Information Technology, Engineering, Data Science, Business, or related field AND 8+ years of experience in data platforms, analytics, AI/machine learning, cloud technologies, technology consulting, software development, solution architecture, and/or practice development; OR equivalent experience. 3+ years of people management experience, including managing technical architects, consultants, or technical specialist teams. 6+ years of experience in a customer-facing technical role, with hands-on experience designing and delivering data and AI solutions. 6+ years of experience leading technical projects, teams, or functions. Technical certifications in data and AI (e.g., Azure AI Engineer Associate, Fabric Analytics Engineer Associate, Fabric Data Engineer Associate, Azure Data Scientist Associate, Azure Solutions Architect Expert, or equivalent). 5+ years of people management experience, including managing technical architects or consulting practice managers.