Senior, Data Engineer
Walmart Global Tech · Posted Oct 13
Software development, cloud infrastructure, and retail technology services for Walmart
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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, from supply chain and merchandising to customer experience and enterprise AI agents. The 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 role designs, builds, and operates batch and streaming data pipelines with Spark, Java, and Python, flexes into platform/software engineering work, and applies AI, GenAI, and agentic capabilities to data platform problems.
What you will do
- Design, build, and operate batch and streaming data pipelines using Spark, Java, and Python, processing data at Walmart scale.
- Apply solid 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 system design and low-level design (LLD) rigor to data and platform problems - evaluating dependencies, trade-offs, failure modes, scalability, and cost before writing a line of code, with support from Staff/Principal engineers on the most ambiguous or cross-team problems.
- Flex into platform/software engineering work when needed: contribute to services, APIs, and distributed systems that data pipelines depend on, working directly in GDF's broader platform codebase.
- Apply AI, GenAI, and agentic capabilities directly to data platform problems: embeddings/vector search for data discovery, LLM-assisted data quality and anomaly detection, agentic pipeline monitoring, 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 actively in architecture and design reviews spanning both data engineering and platform engineering domains, bringing an informed technical point of view.
- As a Senior engineer, bring strong technical judgment to design and code reviews within your immediate team and area of ownership, mentor early-career engineers, and help raise the bar for engineering quality - without needing a formal management title.
- Stay current on emerging Big Data, cloud, and AI/agentic technologies, and propose where they could pragmatically improve reliability, productivity, or business value within your team's scope.
Skills used in this role
What the employer is looking for
- Genuinely hands-on coding: 5+ years of professional software engineering experience with 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.
- Solid 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.
- Solid 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.
- Solid distributed systems fundamentals: event-driven patterns, service contracts, asynchronous processing, and fault tolerance at scale - paired with solid system design and low-level design (LLD) skills, and the ability to evaluate trade-offs, failure modes, scalability, and cost for the components you own.
- Strong software engineering craftsmanship: testing strategy, code review standards, design patterns, and system design for high-throughput data systems.
- Proven ability to translate reasonably well-scoped data/business problems into clear technical execution plans, particularly within a newly formed team - escalating cross-team ambiguity to Staff/Principal engineers as needed.
- Strong ownership mindset and technical judgment; comfortable operating with autonomy within your team in a 0-to-1 environment.
- Minimum Qualifications:Option 1: Bachelor's degree in Computer Science and 3 years' experience in software engineering or related field. Option 2: 5 years' experience in software engineering or related field. Option 3: Master's degree in Computer Science and 1 year's experience in software engineering or related field. 2 years' experience in data engineering, database engineering, business intelligence, or business analytics.
Benefits and support
- incentive awards for your performance
- maternity and parental leave
- PTO
- health benefits
About Walmart Global Tech
Walmart Global Tech is the technological powerhouse and engineering arm of Walmart Inc., responsible for building and managing foundational technologies, cloud infrastructure, and software systems. The organization powers global retail operations across Walmart U.S., Sam's Club, and Walmart International, delivering customer experiences and enterprise services worldwide. Operating across multiple global hubs, it unites engineering, data science, product design, and artificial intelligence to digitally transform retail.
- Industry
- Information Technology
- Company size
- 25000+ employees
- Founded
- 2011
- Location
- Bentonville, Arkansas, USA
- Funding stage
- Public Company
Leadership
Executive Vice President, Global Chief Technology Officer and Chief Development Officer
Executive Vice President, AI Acceleration, Product and Design
Senior Vice President and Tech Operating Partner, Walmart International