Data Engineer III

Position Summary

The Decision Science End-to-End (E2E) team serves Walmart Enterprise Operations. We collaborate across multiple business areas to accelerate data-driven decisions and build lasting analytical capabilities. Strong data foundations are at the core of how we work: we invest in getting the modeling, pipeline design, and data quality right, because everything our partners depend on is built on top of that layer.

We are a lean team, and every member is expected to wear multiple hats. On any given week you might be identifying a new data source, building a pipeline, validating a data model, or walking a business partner through a result. We pride ourselves on full ownership and build partner relationships grounded in trust. Our partners count on us not just to deliver;

we speak up when something needs to change, before they have to ask.

We are seeking a talented and experienced Data Engineer III to join our team. The ideal candidate brings deep experience building reliable data pipelines, designing databases and data models, and transforming raw data into trusted, performant assets that business stakeholders depend on daily. You understand that strong data foundations are not a starting point you move past, they are what you protect and build on throughout your career.

As part of Decision Science E2E, you will contribute across the full data lifecycle, from source identification and modeling to pipeline engineering and stakeholder communication. You will be challenged with complex, ambiguous business problems and collaborate with multiple stakeholders to solve them, gaining a unique perspective on what it takes to operate one of the world's largest retailers.

Understand, articulate, and apply the team's data principles to business problems spanning one or more functions. Champion strong data foundations by ensuring that the models, pipelines, and structures your team builds are correct, documented, and built to last. Help shape how data is governed, structured, and delivered across the areas we support.

Design and build end-to-end data pipelines. Extract data from diverse source systems, transform it into structures fit for analysis and reporting, and load it into targets that power downstream consumers. Stay current on analytics and data engineering trends and bring relevant improvements back to the team.

Identify the most appropriate source for each data problem. Understand priority order of requirements and service level agreements. Perform initial data quality checks on extracted data and validate fitness for purpose before integration.

Analyze complex data elements, systems, data flows, dependencies, and relationships. Develop logical and physical data models including data warehouse and data mart designs. Define relational tables, primary and foreign keys, and stored procedures. Evaluate existing data models and physical databases for variances and discrepancies. Treat every model as a foundational artifact that will outlast any single project.

Write clean, well-tested, and documented production code. Create test cases, build proofs of concept, and deploy software to production. Maintain playbooks and provide timely progress updates to stakeholders.

Wear multiple hats willingly and effectively. Step into gaps where the team needs coverage, whether that is validating a data source, supporting a partner presentation, helping QA a colleague's pipeline, or documenting a process that only lives in someone's head. On this team, ownership extends to what needs doing, not just what is assigned.

Translate ambiguous business problems into concrete data or technical solutions. Identify the right method (analytics, big data, or automation), communicate the approach clearly, and share examples that demonstrate how the solution addresses the business need.

• Education: Bachelor's degree in Computer Science, Information Technology, or a related field; or 5+…