Staff, Data Engineer
Walmart · Posted Oct 13
Retail, e-commerce, grocery, pharmacy, and membership warehouse services
Get a personal compatibility score
Add a resume for personal matches
About the role
GDF (Global Data Foundation) is part of Walmart's AI & Data organization, building the foundational data platforms that power AI, analytics, and decision-making across every Walmart banner and geography. Our newly created platform team is chartered with building next-generation data infrastructure at Walmart scale, including reliable, high-throughput data pipelines and distributed processing systems. This Staff Data Engineer role designs, builds, and operates large-scale batch and streaming data pipelines, contributes to GDF's broader platform codebase, and sets technical direction for data engineering standards.
What you will do
- Design, build, and operate large-scale batch and streaming data pipelines using Spark, Java, and Python, processing data at Walmart scale.
- Apply strong software engineering fundamentals - clean architecture, automated testing, CI/CD, code review discipline - to data engineering work; this is a software engineering role that specializes in data, not a script-writing role.
- Apply domain-oriented design, system design, and low-level design (LLD) rigor to ambiguous data and platform problems - evaluating dependencies, trade-offs, failure modes, scalability, cost, and long-term durability before writing a line of code.
- Flex into platform/software engineering work when needed: build and maintain services, APIs, and distributed systems that data pipelines depend on, contributing directly to GDF's broader platform codebase.
- Integrate AI, GenAI, and agentic capabilities directly into the data platform: embeddings/vector search for data discovery, LLM-assisted data quality and anomaly detection, agentic pipeline monitoring and self-healing, AI-assisted schema and lineage documentation.
- Partner with data scientists and ML engineers to build feature pipelines, model-serving data paths, and the data infrastructure that MLOps depends on.
- Own data quality, observability, and governance for the pipelines and datasets you build, with a strong Operational Excellence / Engineering Excellence discipline.
- Participate in and lead architecture and design reviews spanning both data engineering and platform engineering domains.
- As a Staff engineer, set technical direction and best practices within your team and technical domain without needing a management title - mentor other engineers and influence GDF's broader data engineering standards.
- Continuously evaluate emerging Big Data, cloud, and AI/agentic technologies, adopting them pragmatically where they improve reliability, productivity, or business value.
Skills used in this role
What the employer is looking for
- Genuinely hands-on coding: 8+ years of professional software engineering experience with significant hands-on data engineering at scale; strong proficiency in Java and Python is required, and strong working knowledge of Spark for distributed data processing is required, not optional. Additional experience with Go, C++, or Scala is a plus.
- Operational Excellence (OE) and Engineering Excellence (EE) mindset is a required skill, not a nice-to-have: SLO/SLA ownership, incident management and blameless post-incident reviews, proactive reliability and quality metrics, and continuous improvement built into how you ship, not bolted on afterward.
- Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
- Deep experience with the Big Data ecosystem - Spark, Hadoop/HDFS, Hive, Kafka, workflow orchestration (Airflow or equivalent) - including batch and streaming processing, and large-scale data transformation.
- Strong data platform fundamentals: data modeling, ETL/ELT pipeline design, data quality and observability, data governance, and integration with lakehouse architectures (e.g., Delta Lake, BigQuery, Databricks).
- Full exposure to AI and Agentic technologies: hands-on experience integrating model APIs and GenAI/LLM tooling, building or operating agentic workflows (tool-calling agents, multi-step autonomous systems), working with embeddings/vector search, and applying MLOps practices (feature stores, model lifecycle, retraining pipelines) - not just conceptual awareness.
- Working literacy in platform engineering: microservices, API design, Kubernetes or equivalent orchestration, CI/CD, and cloud-native practices - enough to flex into platform/software engineering work confidently.
- Strong distributed systems fundamentals: event-driven patterns, service contracts, asynchronous processing, and fault tolerance at scale - paired with strong system design, domain-oriented design (DDD), and low-level design (LLD) skills, and demonstrated ability to evaluate trade-offs, failure modes, scalability, and cost when owning production code.
- Strong software engineering craftsmanship: testing strategy, code review standards, design patterns, and system design for high-throughput data systems.
- Proven ability to translate ambiguous data/business problems into clear technical execution plans, particularly within a newly formed team without fully established process.
- Strong ownership mindset and technical judgment; comfortable operating with high autonomy in a 0-to-1 environment.
- 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.
Benefits and support
- Incentive awards for performance
- Maternity and parental leave
- PTO
- Health benefits
About Walmart
Walmart Inc. is an American multinational retail corporation that operates a chain of hypermarkets, discount department stores, and grocery stores. As one of the world's largest companies by revenue, it serves millions of customers daily through physical stores and robust e-commerce platforms. The company is driven by a commitment to everyday low prices and an expanding suite of digital and convenience-focused services.
- Industry
- Retail
- Company size
- 2000000+ employees
- Founded
- 1962
- Location
- Bentonville, Arkansas, USA
- Funding stage
- Public Company
Leadership
President and CEO
Executive Vice President and Chief Financial Officer
Executive Vice President, Global Chief Technology Officer and Chief Development Officer
Executive Vice President and Chief Growth Officer
President and CEO, Walmart U.S.
Recent coverage
The Washington Times
Walmart reiterates pledge against personalized pricing, disputes author's claims on AI, shelf labels2026-10-06
Walmart Corporate
Walmart Grants $15 Million to Feeding America® to Help Strengthen Food Access for Families Across the Country2026-09-30
Walmart Corporate
CITGO® joins the Walmart+ Gas Savings benefit as Walmart adds more member value2026-09-14
AP News
Walmart cautionary with 2026 expectations after sales growth slows2026-08-20