Whole Foods Market is seeking a Data Engineer to join a team responsible for the operational ownership and technical evolution of a mission-critical enterprise data platform powering WFM's core business operations across Finance, Merchandising, Pricing, Supply Chain, and Marketing.
As a Data Engineer, you will be responsible for developing, maintaining, and optimizing business-critical applications and data pipelines that serve 1,600+ active users. You'll work on a complex ERP system built on AWS services, managing everything from data ingestion and ETL processing to report generation and application development. Your work directly impacts WFM's ability to close their books monthly, set prices across 500+ stores, plan promotions, and generate executive KPIs.
This role requires strong technical depth in data engineering fundamentals—database optimization, ETL pipeline development, and data modeling—combined with the ability to work in a fast-paced operational environment where production incidents require immediate response. You'll collaborate closely with business stakeholders in Finance, Merchandising, and Pricing to understand their needs, troubleshoot issues, and deliver solutions that enable data-driven decision making.
You'll work with a diverse technology stack including Amazon Redshift, PostgreSQL/RDS, AWS Glue, S3, Lambda, .NET framework, and various BI reporting tools. This is an opportunity to gain deep expertise in enterprise-scale data systems while making direct business impact on WFM operations.
Key job responsibilities

• Application Development & Maintenance
• Develop and maintain business-critical applications for Finance, Merchandising, Pricing, Supply Chain, and Marketing domains including pricing tools, promotional planning systems, financial reporting, category analytics, and supply chain dashboards
• Build and optimize data pipelines using AWS Glue, Lambda, and custom ETL frameworks; ensure data quality, completeness, and timeliness for critical business workflows
• Create and maintain BI reports and visualizations supporting operational decisions, executive KPIs, and month-end financial close processes
• Implement new features and enhancements based on business partner requirements, balancing technical feasibility with business value
• System Operations & Support
• Provide production support for enterprise data platform including troubleshooting data pipeline failures, database errors, report generation issues, and application defects
• Participate in 24/7 on-call rotation for incident response; resolve critical issues impacting financial close, pricing operations, or business continuity
• Monitor system performance and proactively address bottlenecks in query execution, data processing, and report rendering
• Maintain comprehensive documentation including runbooks, technical specifications, and troubleshooting guides
• Database & Performance Optimization
• Optimize SQL queries, data models, and database structures across Amazon Redshift and PostgreSQL/RDS environments
• Design efficient data schemas supporting complex business logic, historical tracking, and high-volume reporting requirements
• Tune ETL job performance, implement data partitioning strategies, and optimize resource utilization
• Technical Excellence
• Write high-quality, maintainable code following Amazon engineering standards (.NET, Python, SQL)
• Collaborate on infrastructure improvements, security compliance (GDPR/CCPA), and migration to Amazon-native technologies
• Contribute to technical debt reduction, framework stability improvements, and operational efficiency initiatives

Basic Qualifications

• 3+ years of data engineering experience
• 4+ years of SQL experience
• Experience with data modeling, warehousing and building ETL pipelines

Preferred Qualifications

• Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, Fire Hose, Lambda, and IAM roles and permissions
• Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
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