Whole Foods Market is seeking an Data Engineering Manager to lead the ownership and technical evolution of a mission-critical enterprise analytics and operational platform that powers WFM's core business operations across Finance, Merchandising, Pricing, Supply Chain, and Marketing.
As the Data Engineering Manager for Enterprise Data Platform, you will lead an 8-person engineering team responsible for platform operations, system reliability, and continuous improvement of this complex ERP system that serves 1,600+ active users across 43 business-critical applications. You'll own end-to-end platform health—from 24/7 incident response and production support to architectural evolution and strategic modernization initiatives.
This is a high-visibility, high-impact role where you'll be accountable for systems that power month-end financial close, real-time pricing decisions, promotional planning, and executive KPIs. You'll work directly with senior leadership across Finance, Merchandising, Pricing, and Supply Chain, balancing operational excellence with strategic platform evolution. Success in this role means maintaining zero disruption to business operations while driving technical improvements, security compliance, and alignment with Amazon's technology standards.
You'll serve as the technical authority for a platform processing millions of rows of data daily through complex ETL pipelines, managing a diverse technology stack (AWS services, .NET framework, Redshift, PostgreSQL, BI reporting), and ensuring business continuity for WFM's most critical operational systems. This role requires both deep technical expertise and strong leadership—you'll dive deep into production incidents at 2 AM while also presenting quarterly roadmaps to VP-level stakeholders.
Key job responsibilities
Platform Operations & Reliability
• Own 24/7 operational health of an enterprise data platform serving 1,600+ users across 43 business-critical applications (Finance, Merchandising, Pricing, Supply Chain, Marketing)
• Manage production incident response, maintain platform SLAs (99.9%+ uptime), and ensure zero disruption to month-end financial close, pricing operations, and executive reporting
• Drive performance optimization across data pipelines, database queries, and report generation; implement monitoring, alerting, and automation improvements
Technical Leadership
• Provide architecture oversight for complex technology stack: AWS services (Redshift, RDS/PostgreSQL, S3, Glue, Lambda), .NET framework, ETL pipelines, BI reporting
• Lead resolution of systemic technical issues, infrastructure modernization, security compliance (GDPR/CCPA), and alignment with Amazon standards
Team & Stakeholder Management
• Lead, mentor, and develop 8-person Data Engineering team in Bangalore; hire specialized talent in databases, ETL, and BI reporting
• Serve as primary technical interface with VP/Director-level stakeholders across WFM business domains
• Coordinate cross-site collaboration between Bangalore and Austin teams for 24/7 coverage
• Present quarterly roadmaps, operational metrics, and strategic recommendations to GMT leadership
Application Support
• Support diverse applications including pricing tools, promotional planning, financial reporting, category analytics, and supply chain systems
• Manage critical workflows: financial close, pricing updates, promotional campaigns, WBR KPI generation- 2+ years of processing data with a massively parallel technology (such as Redshift, Teradata, Netezza, Spark or Hadoop based big data solution) experience
- 2+ years of relational database technology (such as Redshift, Oracle, MySQL or MS SQL) experience
- 2+ years of developing and operating large-scale data structures for business intelligence analytics (using ETL/ELT processes) experience
- 5+ years of data engineering experience
- Experience managing a data or BI team
- Experience communicating to senior management and customers verbally and in writing
- Experience leading and influencing the data or BI strategy of your team or organization
- Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS- Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
- Experience with AWS Tools and Technologies (Redshift, S3, EC2)
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