• Designs and evolves the data platform using Snowflake, DBT, Sigma, and AWS (Glue, Lambda, SageMaker), ensuring performance, modularity, and scalability for analytics and AI workloads. • Creates and communicates clear architecture direction for software and product team services, which build upon and improve operational effectiveness and efficiencies. • Designs infrastructure and workflows that support machine learning and generative AI use cases, including semantic modeling, feature engineering, and model deployment pipelines. • Identifies trends in technology and anticipates new requirements; recommends and supports strategies to leverage emerging and innovative technologies. • Builds and maintains sandbox environments for experimentation with predictive models, LLMs, and real-time analytics using Snowflake ML and AWS AI services. • Guides integration of machine learning and generative AI into data pipelines and analytics workflows, enabling use cases like semantic search, predictive modeling, and intelligent automation. • Recommends and presents technology applications strategy to meet the current and future needs of respective business areas. • Ensures foundational patterns (e.g., DBT macros, ML preprocessing frameworks) align with enterprise architecture and support AI/ML scalability, governance, and compliance. • Recommends and supports the technical strategy and alignment of data platform capabilities with the business objectives of EMC. • Partners with Data Platform Operations, Information Security, Network, Cloud Engineering, and DevOps teams to lead the design and implementation of new business initiatives as related to data and analytics. • Partners with Platform Operations, Analytics Engineering, and DAP teams to embed AI-ready data platform(s) into data products and ensure alignment with business outcomes. • Serves as a subject matter expert in data analytics platform(s) and AI/ML strategy, influencing platform innovation and guiding teams on best practices for scalable, intelligent data systems. • Serves as a technical resource for Data Platform team members on complex questions or issues. • Designs and recommends software engineering governance policies, procedures, and roles, including proper development techniques and quality management following established SDLC procedures. • Partners with Information Security to create and maintain security and procedures aligned and documented to risk management requirements. • Partners with Enterprise Architecture team to incorporate the creation of patterns and services into reference architecture and SDLC. • Provides guidance for building and maturing assigned solution platforms through automation and reusable processes. • Recommends and supports patterns that guide engineering team members in creating data solutions. • Enhances enterprise engineering practices by sharing expertise in creating engineering processes, alerting, and metrics. • Performs other duties as assigned.