Director of Data Platforms & AI Transformation

Position Summary Headquartered in Plano, TX., Samsung Electronics America, Inc. (SEA) is a leader in mobile technologies, consumer electronics, home appliances and enterprise solutions. From our humble beginnings to our position today as a tech leader, our passion for innovation has been the common thread throughout our history. We’ve grown into one of THE most recognized global brands. We consider ourselves “relentless pioneers” that push boundaries and defy barriers. The company pushes beyond the limits of today’s technology to provide groundbreaking connected experiences across its large portfolio of products and services, including mobile devices, home appliances, home entertainment, 5G networks, and digital displays. As EPA’s ENERGY STAR® Corporate Commitment Partner, SEA is dedicated to making a positive impact on the environment through its eco-conscious products, practices, and operations. People | Excellence | Change | Integrity | Co-Prosperity Role and Responsibilities Samsung Electronics is seeking an innovative, highly strategic technologist and operational leader to fill the role of Director of B2B Data Platforms & AI Transformation. This pivotal position sits at the intersection of enterprise data infrastructure, business intelligence, and advanced AI automation systems. The successful candidate will own the strategic direction, technical governance, maintenance, and end-to-end optimization of our core enterprise data ecosystems (Claude, Salesforce, Tableau BI platforms, and multidimensional data cubes/repositories). Concurrently, this leader will aggressively spearhead our AI transformation roadmap, deploying agentic frameworks and workflows to drive unprecedented operational efficiencies, remove manual reporting bottlenecks, and automate cross-functional metrics across regional and global operations. Strategic Objective: Transform B2B’s data estate from a series of passive storage and reporting layers into a highly integrated, intelligent ecosystem that leverages AI automation to provide proactive insights directly into executive reporting pipelines and SCM workflows. Core Responsibilities 1. AI Transformation & Intelligent Automation  Drive Efficiency Roadmaps: Architect and execute an enterprise-wide AI transformation strategy focused on automating manual legacy data reporting systems and compressing data-to-insights cycles. Agentic Frameworks & Workflows: Evaluate, design, deploy, and govern intelligent AI agents (including Salesforce Agentforce tools and customized LLM layers) to manage automated data verification, conversational analytics, and anomaly detection. Operational Modernization: Modernize traditional reporting mechanisms across divisions by establishing automated workflows that deliver predictive insights natively within standard operational software. 2. Enterprise Data Ecosystem & Infrastructure Management  Salesforce Systems Management: Oversee the structural integrity, data hygiene, and optimization of the Salesforce CRM platform as a primary enterprise customer and sales data engine. Advanced Analytics & Business Intelligence: Serve as the executive product owner for Tableau (Cloud and Server environments), establishing enterprise semantic layers, unified metadata definitions, and master data guidelines. Data Repository & Cube Optimization: Supervise the maintenance, performance tuning, and structural scaling of multidimensional data repositories (OLAP cubes, data lakes, and modern lakehouse frameworks) to ensure sub-second query performance for highly complex reporting dashboards. 3. Change Management & Cross-Functional Leadership  Matrix Stakeholder Alignment: Partner extensively with business owners across Sales, Supply Chain Management (SCM), Revenue Operations, and Finance to align analytical models and standardize data governance protocols. Data Culture Cultivation: Lead technical change management frameworks to upskill business units, transitioning standard business analysts away from manual data preparation toward AI-assisted self-service analytical pipelines. 4. Team Leadership & Talent Engineering Manage Talent: Lead, recruit, and mentor a high-performing team consisting of senior data engineers, BI architects, platform managers, and AI workflow optimization specialists. Culture of Agility: Foster a culture of technical agility, continuous learning, and strict data privacy compliance across all AI operations. Skills and Qualifications Required Qualifications & Competencies Experience & Education Professional Experience: Minimum of 10–12+ years of progressive technical experience in Data Engineering, Enterprise Platform Architecture, or Business Intelligence. Leadership Record: 5+ years of dedicated team leadership, managing multi-disciplinary engineering or data platforms teams within a large, multi-national matrix organization. Education: Bachelor's or Master's degree in Computer Science, Data Science, Information Systems, or a related quantitative field. An MBA paired with a technical background is highly desirable. Technical & Functional Competencies Ecosystem Proficiency: Demonstrated architectural-level command over Salesforce CRM and Tableau BI ecosystem deployment, security protocols, and API scaling. Data Architecture Expertise: Hands-on experience scaling enterprise data repositories AI & ML Integration: Thorough, up-to-date knowledge of enterprise AI integration paradigms, metadata orchestration, LLM context windows, semantic caching, and building closed-loop agentic automations. Core Leadership Traits Executive Communication: Outstanding capabilities in translating intricate, highly technical backend architecture details into clear, value-oriented business impact metrics for C-suite and executive vice president stakeholders. Strategic Problem-Solving: Strong analytical and change-management focus, capable of dissolving historical data silos and harmonizing disparate global busine