(IND) STAFF, DATA ENGINEER
Confirmed on the employer's own hiring board on Nov 2, 2026. First seen by Alion on Oct 29, 2026. Walmart scores A on the Alion truth index.
Position Summary...
We're looking for a Staff Data Engineer to own the pipelines, data models, and data platform decisions that power our business. This is a senior individual-contributor role - you won't manage people, but you'll be trusted to build, integrate, and harden production data infrastructure independently, review the work of engineers around you, and make architectural calls that hold up under scale.What you'll do...
About Team
GDF (Global Data Foundation) is part of Walmart's AI & Data organization - the team building the foundational data platforms that power AI, analytics, and decision-making across every Walmart banner and geography, from supply chain and merchandising to customer experience and enterprise AI agents. Our newly created platform team is chartered with building next-generation data infrastructure at Walmart scale: reliable, high-throughput data pipelines, distributed processing systems, and platform capabilities that downstream teams across Walmart depend on every day.
What You'll Do
- Problem Formulation: Translate business problems into data-driven solutions, choosing the right methods and tools and explaining how they solve the problem.
- Business Context: Turn business requirements into concrete projects with clear ROI, acting as the bridge between business needs and technical solutions.
- Data Source Identification: Identify and vet the best-fit internal/external data sources against SLAs and quality standards, and guide junior engineers on sourcing decisions.
- Data Transformation & Integration: Design and automate ETL/ELT pipelines across diverse sources, deploy them via orchestration frameworks, and catch data-quality risks early.
- Data Modeling: Build and maintain logical/physical data models across relational, dimensional, and NoSQL platforms, and set modeling standards the team can reuse.
- Code Development & Testing: Review designs and code, choose the right languages and testing approach, fix scalability issues, and keep production stable.
- Data Governance: Establish and implement data-governance practices, interpret policy for the team, and keep documentation and standards current.
- Data Strategy: Apply the org's data strategy to moderately complex, cross-functional business problems.
Semantic Modeling & Enterprise Data Architecture
- Lead the design of scalable conceptual, logical, and physical data models for operational, analytical, and AI/ML use cases.
- Define and implement dimensional models - conformed dimensions, fact tables, SCD Type 1 and Type 2 patterns, snapshots, event models, and data-product contracts.
- Design and maintain a governed semantic layer that standardizes business metrics, calculations, hierarchies, joins, definitions, and security policies across BI, self-service analytics, and AI applications.
- Establish modeling standards for naming, grain, keys, lineage, audit columns, partitioning, clustering, retention, and data-quality controls.
- Partner with domain teams to translate business processes into reusable, certified datasets and semantic models.
- Build and optimize transformation pipelines using SQL and modern data-engineering frameworks.
- Enable self-service analytics through certified metrics, reusable dimensions, governed views, and documentation.
- Drive data-governance practices including data classification, row- and column-level security, privacy controls, access patterns, metadata, and lineage.
- Review architecture and data-model designs, identify risks, and guide teams toward scalable, maintainable solutions.
- Define quality and observability measures - reconciliation, freshness, completeness, metric consistency, and schema-change monitoring.
- Mentor engineers and analysts in data modeling, semantic design, and engineering best practices.
- Influence enterprise data architecture strategy and technology decisions across data platforms, BI tools, and AI applications.
What you will bring :
12+ years of professional data engineering experience (or equivalent demonstrated impact). Semantic and dimensional modeling expertise is a core, must-have requirement for this role - not a nice-to-have.
- Deep, hands-on expertise in dimensional data modeling - facts, dimensions, grain, surrogate keys, conformed dimensions, SCD Type 1/2 patterns, and snapshot modeling.
- Proven track record designing and governing semantic models and certified metrics for BI and self-service analytics platforms, including modeling tools such as Erwin.
- Extensive experience building logical and physical data models across relational, dimensional, and NoSQL platforms, with modeling standards other engineers can reuse.
- Strong hands-on expertise in Python and SQL.
- Production experience with Apache Spark, Apache Hive, and Scala for large-scale data processing.
- Hands-on experience with Azure and Google BigQuery (GBQ) cloud data platforms.
- Experience building, deploying, and operating pipelines with orchestration frameworks (e.g., Airflow, Dagster, or equivalent).
- Hands-on experience with Apache Kafka or equivalent for real-time streaming data pipelines.
- Proven experience implementing data quality frameworks and ensuring compliance and data governance across the data lifecycle.
- Demonstrated ability to review and guide the work of other engineers, even without formal management authority.
- Demonstrated ability to lead cross-functional technical initiatives and influence senior engineering and business stakeholders.
- Strong stakeholder communication skills - comfortable translating business asks into technical solutions and back.
- Experience working with Agentic AI frameworks (e.g., LangChain, LangGraph, AutoGen) to build autonomous or LLM-driven data workflows.
- Working knowledge of CI/CD practices and automated deployment pipelines (e.g., Jenkins, GitHub Actions, Azure DevOps).
Added Advantage & Preferred
- Strongly preferred: hands-on experience with semantic-layer or BI technologies such as Looker/LookML, Cube, AtScale, Power BI, or Tableau to deliver governed, certified metrics.
- Experience designing data products for AI, machine learning, agentic applications, or retrieval-based systems.
- Experience with healthcare, retail, financial, or other regulated data domains.
- Experience implementing privacy-aware data access patterns, including masking, policy tags, authorized views, and role- or attribute-based access controls.
- Experience with event-driven data, CDC pipelines, streaming platforms, or lakehouse architectures.
- Familiarity with data catalog, lineage, observability, and data-quality platforms.
- Working knowledge of Java or React.js - preferred.
About Walmart Global Tech Imagine working in an environment where one line of code can make life easier for hundreds of millions of people. That’s what we do at Walmart Global Tech. We’re a team of software engineers, data scientists, cybersecurity expert's and service professionals within the world’s leading retailer who make an epic impact and are at the forefront of the next retail disruption. People are why we innovate, and people power our innovations. We are people-led and tech-empowered.
We train our team in the skillsets of the future and bring in experts like you to help us grow. We have roles for those chasing their first opportunity as well as those looking for the opportunity that will define their career. Here, you can kickstart a great career in tech, gain new skills and experience for virtually every industry, or leverage your expertise to innovate at scale, impact millions and reimagine the future of retail.
Walmart’s culture sets us apart, and we know being together helps us innovate, learn and grow great careers. This role is based in our Bangalore office for daily work, with the flexibility for associates to manage their personal lives.
Benefits
Beyond our great compensation package, you can receive incentive awards for your performance. Other great perks include a host of best-in-class benefits maternity and parental leave, PTO, health benefits, and much more.
Belonging
We aim to create a culture where every associate feels valued for who they are, rooted in respect for the individual. Our goal is to foster a sense of belonging, to create opportunities for all our associates, customers and suppliers, and to be a Walmart for everyone.
At Walmart, our vision is "everyone included." By fostering a workplace culture where everyone is-and feels-included, everyone wins. Our associates and customers reflect the makeup of all 19 countries where we operate. By making Walmart a welcoming place where all people feel like they belong, we’re able to engage associates, strengthen our business, improve our ability to serve customers, and support the communities where we operate.
Equal Opportunity Employer
Walmart, Inc., is an Equal Opportunities Employer - By Choice. 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 understanding, respecting and valuing unique styles, experiences, identities, ideas and opinions - while being inclusive of all people.
Minimum Qualifications...
Outlined below are the required minimum qualifications for this position. If none are listed, there are no minimum qualifications.
Minimum Qualifications:Option 1: Bachelor's degree in Computer Science and 4 years' experience in software engineering or related field. Option 2: 6 years' experience in software engineering or related field. Option 3: Master's degree in Computer Science and 2 years' experience in software engineering or related field. 3 years' experience in data engineering, database engineering, business intelligence, or business analytics.Preferred Qualifications...
Outlined below are the optional preferred qualifications for this position. If none are listed, there are no preferred qualifications.