STAFF, DATA ENGINEER at Walmart

Job description

Position Summary... Staff Data engineer for Real Estate and Customer Care area 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 • 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. What You'll Bring • 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 workf