Senior Manager, AI & Data Analytics

Samsung•Plano, TX

1d•Onsite

About The Position

Samsung Electronics America, Inc. (SEA) is seeking a highly versatile and analytically driven AI Analytics leader to join their Data & AI Analytics organization. This is a business-side role focused on deriving business insights from data, engineering scalable infrastructure, and architecting an enterprise data platform. The role operates within a GCP-native environment, utilizing Google Cloud's data and AI services. The position involves hands-on contribution to SEA's AI and agentic development practice, building intelligent workflows. The Senior Manager will lead a team of 3-4 analysts/contractors, manage stakeholders across a matrixed organization, and drive data and AI initiatives from ideation to business impact. The role requires 8-15 years of combined experience in data analysis, data engineering, and data architecture, with a blend of technical depth, business strategy, and people leadership.

Requirements

Bachelor's degree in Computer Science, Data Science, Data Engineering, Information Systems, Statistics, Mathematics, or a related quantitative field.
8-15 years of combined hands-on experience spanning data analysis, data engineering, and data architecture in a production, cloud-native environment.
Deep expertise in Google BigQuery (advanced SQL, query optimization, partitioning/clustering, dataset design, cost governance).
Proficiency in Python for data engineering, pipeline development, data manipulation, and automation scripting.
Hands-on experience with at least three of: Google Dataflow, Cloud Composer (Airflow), Pub/Sub, Dataproc, Cloud Storage, or Cloud Functions.
Strong experience with dbt (data build tool) for data transformation, modeling, testing, and analytics engineering.
Experience with Looker and/or Looker Studio for dashboard development and self-serve analytics.
Demonstrated experience with GCP data governance tooling (Google Dataplex, Data Catalog, or equivalent).
Experience with Terraform or equivalent Infrastructure as Code tools.
Hands-on experience integrating AI/ML APIs into data workflows (Vertex AI, Gemini, or equivalent LLM APIs).
Working knowledge of AI agent frameworks (LangChain, LangGraph, Google ADK, or CrewAI).
Understanding of RAG architecture (vector embeddings, semantic retrieval, chunking strategies, and evaluation).
Strong understanding of data modeling paradigms (relational, dimensional, and NoSQL).
Deep knowledge of cloud data security (IAM, VPC Service Controls, column-level security, data masking, encryption, and regulatory compliance like CCPA, GDPR, SOX).
Experience directly managing or leading a team of 2 or more analysts, engineers, or data professionals.
Experience managing external contractors or vendor resources.

Responsibilities

Design and execute end-to-end analyses on large, complex datasets to answer strategic business questions across various segments (consumer electronics, mobile, home appliances, eCommerce, B2B).
Translate findings into clear, actionable recommendations for senior stakeholders.
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.
Communicate complex analytical findings through compelling narratives and visualizations.
Monitor, validate, and enforce data quality across analytical datasets; partner with Engineering to resolve issues and establish data SLA standards.
Design, build, and maintain scalable batch and real-time ELT/ETL data pipelines using Google Dataflow, Cloud Composer, Pub/Sub, and dbt.
Develop and maintain BigQuery datasets, tables, and data models, applying best practices for performance and cost-optimization.
Integrate structured and unstructured data from diverse sources into SEA's centralized GCP data platform.
Manage GCP data infrastructure using Terraform, enforcing IaC principles.
Implement data quality checks, pipeline SLA monitoring, and alerting using Cloud Monitoring and dbt tests.
Design and govern the end-to-end data architecture for SEA on GCP, ensuring alignment with business strategy and global Samsung standards.
Lead the design and implementation of data mesh principles at SEA using GCP Dataplex.
Own SEA's data catalog and metadata strategy using Google Data Catalog and Dataplex.
Architect and enforce data security controls across the GCP stack, ensuring compliance with CCPA, GDPR, SOX, and Samsung global data compliance requirements.
Define and enforce architectural standards, design patterns, and best practices for data engineering and analytics development.
Design the foundational architecture for AI and generative AI workloads on GCP, including Vertex AI Feature Store, vector database design, and AI data pipeline patterns.
Build and deploy AI agents and multi-agent systems using LangChain, LangGraph, and Google ADK.
Design and implement Retrieval-Augmented Generation (RAG) pipelines connecting BigQuery and Vertex AI Vector Search.
Integrate Vertex AI Generative AI and Gemini APIs into analytics and data pipelines.
Support Data Science teams by building feature engineering pipelines and managing data feeds to Vertex AI Feature Store.
Apply prompt engineering best practices and develop evaluation frameworks for LLM output quality.
Directly manage a team of 3-4 analysts and data professionals, setting goals, providing coaching, and ensuring accountability.
Oversee and manage external contractors and vendor resources.
Navigate Samsung's complex, matrixed global organization to align stakeholders.
Drive adoption of data-driven decision-making and AI-powered workflows through influence and partnership.
Act as the senior Data & AI partner for assigned SEA business lines, identifying opportunities to leverage data and AI.
Communicate data and AI strategy, progress, and outcomes clearly to various audiences.
Author and maintain architecture decision records (ADRs), data contracts, and team playbooks.