Data Engineer | Bentonville, Arkansas, United States Job Summary: Data Engineer (Onsite - Northwestern Arkansas) About the Role Join a dynamic team powering large-scale demand forecasting and Machine Learning Operations (ML Ops) at a leading enterprise in Northwestern Arkansas. As a Data Engineer, you will design and optimize critical data pipelines, collaborate with top-tier AI experts, and impact supply chain innovation from end to end. This is a unique opportunity to apply advanced data engineering skills in a high-visibility, growth-focused environment. Responsibilities - Design, build, and maintain scalable ETL/ELT pipelines using Apache Airflow, Apache Spark, and GCP Dataflow. - Develop and optimize data models, schemas, and complex SQL queries in BigQuery. - Build robust data pipelines supporting AI/ML feature stores and forecasting models. - Partner with AI Developers to deliver high-quality, low-latency data for model training and inference. - Implement and manage Cloud Composer DAGs and orchestrate data workflows for reliability. - Establish data quality monitoring, alerting, and lineage tracking solutions. - Participate in data platform architecture and contribute to technical documentation. - Support backend software engineering and DevOps tasks for the data platform. Required Skills and Experience - 3+ years (intermediate) or 5+ years (specialist) in Data Engineering. - Hands-on expertise with Apache Airflow for pipeline orchestration. - Proficient in Apache Spark for large-scale data processing. - Strong SQL abilities, with deep knowledge of BigQuery optimization. - Experience working with Google Cloud Platform (GCP) services: BigQuery, Cloud Storage, Pub/Sub, Dataflow. - Solid understanding of ETL/ELT and data warehousing best practices. - Must be authorized to work in the US without current or future sponsorship. Preferred Skills - GCP Professional Data Engineer certification. - Experience supporting ML/AI infrastructure, feature engineering, and model training datasets. - Familiarity with real-time streaming (Kafka, Flink). - Experience in retail or large-scale consumer data environments. Benefits - Competitive compensation. - 4 days onsite fosters collaboration and meaningful team engagement. - Exposure to cutting-edge ML Ops initiatives and end-to-end supply chain systems. - Opportunity for career advancement in a rapidly growing, AI-focused organization. - Work on high-impact projects with industry leaders. How to Apply Ready to accelerate your data engineering career? Submit your resume and a brief cover letter outlining your relevant experience. Qualified candidates will be contacted for next steps. Background check and drug screen required.