Senior Manager, AI & Data Analytics

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

Samsung Electronics America is seeking a highly versatile and analytically driven AI Analytics leader to join our Data & AI Analytics organization. This is a unique, high-impact business-side role designed for a professional who can operate across the full data spectrum -- deriving sharp business insights from data, engineering the scalable infrastructure that powers those insights, and architecting the enterprise data platform that ensures everything is governed, trusted, and future-proof.



You will work within a fully GCP-native environment, leveraging the breadth of Google Cloud's data and AI services -- from BigQuery and Dataflow to Vertex AI and Gemini -- to deliver end-to-end data capabilities across SEA's consumer electronics, eCommerce, and B2B business lines. You will also be a hands-on contributor to SEA's growing AI and agentic development practice, building intelligent, automated workflows that amplify the value of data across the organization.



As a Senior Manager, you will directly manage a team of 3-4 analysts and/or contractors, navigate Samsung's matrixed global organization to align stakeholders across regional and HQ boundaries, and drive data and AI initiatives from ideation to business impact. You bring 8-15 years of combined experience across data analysis, data engineering, and data architecture, and you thrive where technical depth meets business strategy and people leadership.

Role and Responsibilities

Data Analysis & Business Insights

• Analytics Ownership: Design and execute end-to-end analyses on large, complex datasets to answer strategic business questions across consumer electronics, mobile, home appliances, eCommerce, and B2B segments; translate findings into clear, actionable recommendations for senior stakeholders.
• Dashboards & Reporting: Build, own, and continuously improve interactive dashboards and self-serve reporting solutions in Looker and Looker Studio; define metrics, KPIs, and business logic in alignment with stakeholder needs.
• Data Storytelling: Communicate complex analytical findings through compelling narratives and visualizations tailored to both technical and non-technical audiences including executive leadership.
• Data Quality Stewardship: Monitor, validate, and enforce data quality across analytical datasets; partner with Engineering to resolve root cause issues and establish data SLA standards.

Data Engineering & Pipeline Development

• Pipeline Design & Development: Design, build, and maintain scalable batch and real-time ELT/ETL data pipelines using Google Dataflow (Apache Beam), Cloud Composer (Apache Airflow), Pub/Sub, and dbt; ensure pipelines are performant, observable, testable, and production-grade.
• BigQuery Data Modeling: Develop and maintain BigQuery datasets, tables, and data models; apply dimensional modeling, partitioning, clustering, and cost-optimization best practices to serve both analytical and operational workloads at SEA scale.
• Data Ingestion & Integration: Integrate structured and unstructured data from diverse sources -- APIs, operational databases, event streams, third-party SaaS platforms, and IoT/SmartThings device data -- into SEA's centralized GCP data platform.
• Infrastructure as Code: Manage GCP data infrastructure using Terraform; enforce IaC principles to ensure reproducibility, version control, and environment consistency across development, staging, and production.
• Observability & Reliability: Implement data quality checks, pipeline SLA monitoring, and alerting using Cloud Monitoring and dbt tests; own pipeline reliability and participate in on-call escalation for critical data flows.