Head of Semantic Data Engineering

Overview

Position Summary... What you'll do...The Mission At Sam’s Club, we are no longer just building dashboards or static pipelines; we are building the "brain" of the retail experience. As the Senior Engineering Manager for Agentic Data, you will be at the forefront of the AI revolution. Your mission is to evolve our massive data ecosystem into a Semantic & Contextual Layer—the foundational intelligence that allows AI Agents to reason, plan, and act autonomously for millions of members.

You aren t just managing a team; you are architecting the bridge between raw data and autonomous action. You will lead the transition from traditional data structures to agent-ready environments, where data is not just stored, but understood in real-time.

• Architect the Semantic Future:
  Define the technical vision for a unified semantic layer that transforms structured, semi-structured, and unstructured data into context-aware representations (Embeddings, Knowledge Graphs, and Metadata) consumable by LLMs and multi-agent workflows.
• Real-Time Agentic Intelligence:
  Own the streaming architecture that feeds our agents. You will leverage Kafka to build low-latency event-driven pipelines, ensuring agents have access to "up-to-the-second" member context and environmental state.
• Champion Data Fundamentals:
  Ensure the bedrock of our AI strategy is built on elite Data Engineering principles. You will oversee the design of scalable schemas, partitioning strategies, and high-performance indexing that make petabyte-scale data accessible to reasoning models.
• Build Agent-Ready Ecosystems:
  Lead the design of "Agentic Data" pipelines—ensuring that data provided to AI agents is high-fidelity, optimized for retrieval, and enriched with the necessary business logic to prevent hallucinations.
• Strategic Leadership:
  Manage and mentor a high-performing team of engineers. You will bridge the gap between AI/ML Research, Product, and Platform Engineering to align data roadmaps with long-term autonomous decision-making goals.
• Innovate Retrieval Systems:
  Own the strategy for Retrieval-Augmented Generation (RAG) at scale, optimizing how our agents discover and interact with Sam s Club’s vast proprietary knowledge base across both batch and streaming sources.
• Establish Operational Excellence:
  Define standards for "Agentic Observability"—implementing telemetry, lineage, and auditability patterns specifically for autonomous and regulated AI workflows.

• Experience:
  
  7–10+ years in Data Engineering, building and operating large-scale, distributed, fault-tolerant data platforms, with at least 3+ years in a leadership role.
• Data Engineering Mastery:
  Deep-rooted expertise in Data Fundamentals. You must be an expert in data modeling (Star/Snowflake, Data Vault), storage formats (Parquet, Avro), and distributed computing concepts (sharding, replication, and CAP theorem).
• Real-Time Expertise:
  Deep experience with Kafka and event-driven architectures. You understand how to manage state, schema evolution, and consistency in streaming environments (Kafka Streams, Flink, or Spark Streaming).
• Semantic & AI Mastery:
  Deep familiarity with the modern AI stack—specifically Vector Databases (Pinecone, Milvus), Knowledge Graphs, and framework orchestration (Lang Chain, Llama Index, CrewAI).
• Cloud Scale Mastery:
  Proven track record in GCP or Azure, utilizing Big Query, Dataflow, and Pub/Sub to handle petabyte-scale workloads.
• Data Modeling for LLMs:
  Expert-level understanding of how schema choices, latency, and context window management impact AI reasoning and retrieval quality.
• Engineering Rigor:
  Fluency in Python, Java, or Scala, with a deep engineering mindset around testability, maintainability, and high-performance system design.

Beyond competitive pay, you can receive incentive awards for your performance. Other great perks include 401(k) match, stock purchase plan, paid maternity and parental leave, PTO, multiple health plans, and much more.

We believe we are best equipped to help our associates, customers and the communities we serve live better when we really know them. That means…