Senior Manager, AI & Data Analytics

Samsung Electronics•Plano, TX

2d•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 Senior Manager will be a hands-on contributor to SEA's AI and agentic development practice, building intelligent, automated workflows. The position involves managing a team, navigating a global organization, and driving data and AI initiatives from ideation to business impact. The ideal candidate has 8-15 years of experience in data analysis, data engineering, and data architecture, combining technical depth with 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, and cross-project topology.
Proficiency in Python for data engineering, pipeline development, data manipulation, and automation scripting.
Hands-on experience with GCP data pipeline services -- including 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, semantic data modeling, and self-serve analytics.
Demonstrated experience with GCP data governance tooling -- Google Dataplex, Data Catalog, or equivalent -- for metadata management, data lineage, and federated governance.
Experience with Terraform or equivalent Infrastructure as Code tools for managing cloud data infrastructure.
Hands-on experience integrating AI/ML APIs into data workflows -- including calling Vertex AI, Gemini, or equivalent LLM APIs as part of automated pipelines or analytical tools.
Working knowledge of AI agent frameworks (LangChain, LangGraph, Google ADK, or CrewAI) and the ability to build or extend agentic data workflows with tool use and RAG capabilities.
Understanding of RAG architecture -- vector embeddings, semantic retrieval, chunking strategies, and evaluation.
Strong understanding of data modeling paradigms: relational, dimensional, and NoSQL; ability to select and apply the right model to the right problem.
Deep knowledge of cloud data security: IAM, VPC Service Controls, column-level security, data masking, encryption, and regulatory compliance (CCPA, GDPR, SOX).
Experience directly managing or leading a team of 2 or more analysts, engineers, or data professionals -- including setting goals, conducting performance reviews, and developing talent.
Experience managing external contractors or vendor resources -- including scoping work, managing deliverables, and ensuring quality and compliance.

Responsibilities

Design and execute end-to-end analyses on large, complex datasets to answer strategic business questions across various segments; 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.
Communicate complex analytical findings through compelling narratives and visualizations tailored to both technical and non-technical audiences.
Monitor, validate, and enforce data quality across analytical datasets; partner with Engineering to resolve root cause 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, partitioning, clustering, and cost-optimization.
Integrate structured and unstructured data from diverse sources into SEA's centralized GCP data platform.
Manage GCP data infrastructure using Terraform; enforce IaC principles for reproducibility, version control, and environment consistency.
Implement data quality checks, pipeline SLA monitoring, and alerting using Cloud Monitoring and dbt tests; own pipeline reliability and participate in on-call escalation.
Design and govern the end-to-end data architecture for SEA on GCP, ensuring alignment with business strategy, scalability, and global Samsung standards.
Lead the design and implementation of data mesh principles at SEA using GCP Dataplex, defining data domains, ownership, governance, and self-serve access.
Own SEA's data catalog and metadata strategy using Google Data Catalog and Dataplex; define tagging, lineage capture, PII classification, and business glossary standards.
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 all data engineering and analytics development at SEA.
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 with Gemini/PaLM APIs.
Integrate Vertex AI Generative AI and Gemini APIs directly into analytics and data pipelines.
Support Data Science teams by building feature engineering pipelines, managing data feeds to Vertex AI Feature Store, and maintaining model input/output schemas.
Apply prompt engineering best practices and develop evaluation frameworks to assess LLM output quality, agent reliability, and RAG retrieval accuracy.
Directly manage a team of 3-4 analysts and data professionals, setting goals, providing coaching, and holding the team accountable.
Oversee and manage external contractors and vendor resources, defining scopes of work, managing deliverables, and evaluating performance.
Navigate Samsung's complex, matrixed global organization, building relationships and aligning stakeholders across regional and HQ boundaries.
Drive adoption of data-driven decision-making and AI-powered workflows across business units through influence and partnership.
Act as the senior Data & AI partner for assigned SEA business lines, identifying opportunities to leverage data and AI to solve business problems.
Communicate data and AI strategy, progress, and outcomes clearly to various audiences, translating technical complexity into business-relevant language.
Author and maintain architecture decision records (ADRs), data contracts, analytical methodology documentation, and team playbooks.