Senior Manager, AI & Data Analytics
On-sitePlano, Texas, United States
Job Summary
Design and execute end-to-end analyses on large datasets across consumer electronics, mobile, and B2B segments to translate findings into actionable recommendations for senior stakeholders. Build, own, and continuously improve interactive dashboards and self-serve reporting solutions in Looker and Looker Studio while defining metrics and KPIs aligned with stakeholder needs. Monitor, validate, and enforce data quality across analytical datasets, partnering with Engineering to resolve root cause issues and establish data SLA standards. Design, build, and maintain scalable batch and real-time ELT/ETL pipelines using Google Dataflow, Cloud Composer, and dbt to ensure production-grade performance and observability. Manage GCP data infrastructure using Terraform, design the foundational architecture for AI and generative AI workloads on GCP, and build AI agents and multi-agent systems using LangChain and Google Agent Development Kit. Directly manage a team of 3-4 analysts and contractors, set clear goals and priorities, and provide ongoing coaching and performance development. Navigate Samsung's matrixed global organization to align stakeholders across regional and HQ boundaries, driving data and AI initiatives from ideation to business impact.
Required Qualifications
- 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 evaluating performance
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