Principal, Data Architect

About the role

At Sam's Club, we offer competitive pay as well as performance-based bonus awards and other great benefits for a happier mind, body, and wallet!

Health benefits include medical, vision and dental coverage.

Financial benefits include 401(k), stock purchase and company-paid life insurance.

Paid time off benefits include PTO, parental leave, family care leave, bereavement, jury duty, and voting.

You will also receive PTO and/or PPTO that can be used for vacation, sick leave, holidays, or other purposes.

The amount you receive depends on your job classification and length of employment.

It will meet or exceed the requirements of paid sick leave laws, where applicable.

For information about PTO, see https://one.walmart.com/notices.

Other benefits include short-term and long-term disability, company discounts, Military Leave Pay, adoption and surrogacy expense reimbursement, and more.

Live Better U is a company paid education benefit program for full-time and part-time associates in Walmart and Sam's Club facilities. Programs range from high school completion to bachelor's degrees, including English Language Learning and short-form certificates.

Tuition, books, and fees are completely paid for by Walmart.

Eligibility requirements apply to some benefits and may depend on your job classification and length of employment.

Benefits are subject to change and may be subject to a specific plan or program terms.

What you'll do...

• Arcitect the Semantic World Model: Lead the design of a global semantic layer that unifies structured, semi structured, and unstructured data into shared, context aware representations (Knowledge Graphs and Metadata Tensors) optimized for LLM reasoning.
• Design for Real Time State: Define the architecture for persistent agent memory and real time state management. Ensure agents have a seamless "mental model" that synchronizes a member’s current session with their long term history across all channels.
• Establish the Tool-Calling Fabric: Transition the enterprise from "Data-as-a-Table" to "Data-as-a-Tool for Agentic Enablement". Design the architectural contracts and schemas that allow agents to call data products as executable functions with deterministic outcomes.
• Lead the Agentic Reference Architecture: Define and steward enterprise standards for Agent Ready Data. This includes creating reference patterns for GraphRAG (Graph-Augmented Generation), vector space optimization, and hierarchical ontology design.
• Enable Model-Agnostic Intelligence: Build a decoupled semantic interface that ensures our data strategy remains stable and performant regardless of the underlying LLM or agent framework being utilized.
• Architect Trust & Grounding: Design "Reasoning Guardrails" into the data layer. Ensure that the semantic architecture provides verifiable grounding for AI actions, minimizing hallucinations through strict policy enforcement and deterministic data paths.
• Strategic Influence & Modernization: Partner with Engineering, AI/ML, and Product leaders to drive an AI-native operating model. Lead the technical roadmap for modernizing legacy systems into composable, intelligent platforms.

What You’ll Bring

• 10–15+ years of experience in large scale distributed data architecture, with a proven track record of shaping enterprise level data strategies.
• Architectural Fluency in Agentic Systems: Deep expertise in the "Context Stack"—including Vector Databases, Enterprise Knowledge Graphs, and the orchestration of multi agent workflows.
• Semantic Mastery: Expert level knowledge of Ontology Engineering and Metadata Management. You understand how to mathematically represent business logic so it is computable by a model.
• Real Time Architecture Expertise: Deep understanding of real time event processing and how to blend high volume streaming data with analytical stores to provide agents with "Total Recall."
• Systems Thinking: Ability to reason about the trade-offs between latency, information density, and token cost when designing data structures for LLM context windows.
• Engineering Foundation: Strong hands on experience across the modern data and AI stack: Core & Distributed Systems: Python, Java, or Scala; Databricks, Spark, and BigQuery. Real Time & Streaming: Kafka, Druid, and streaming frameworks like Spark Structured Streaming, Kafka Connect, or Apache Flink. Agentic Frameworks & Protocols: MCP Server, LangChain/LangGraph, Prompt Engineering, and Multimodal AI. Orchestration & Semantics: Camunda for workflow logic, LookML for metrics modeling, and deep familiarity with GCP or Azure cloud native ecosystems.
• Leadership through Architecture: Demonstrated ability to align diverse stakeholders and influence technical direction across organizational boundaries without direct authority.

Minimum Qualifications

• Option 1: Bachelor’s degree in Computer Science or related field and 5 years' experience in data engineering, solution architecture, business intelligence, business analytics or related field.
• Option 2: 7 years' experience in data engineering, solution architecture, business intelligence, business analytics or related field.
• Option 3: Master's degree in Computer Science and 3 years' experience in data engineering, solution architecture, business intelligence, business analytics or related field.

Preferred Qualifications

• Data architecture/software architecture/data modeling, Master’s degree in Computer Science or related field and 5 years' experience in software engineering or related field,
• Relevant industry experience (for example, retail, supply chain, eCommerce, healthcare, etc.),
• Solution Architecture,
• We value candidates with a background in creating inclusive digital experiences, demonstrating knowledge in implementing Web Content Accessibility Guidelines (WCAG) 2.2 AA standards, assistive technologies, and integrating digital accessibility seamlessly.