Sr Business Analyst, Competitive Intelligence, Whole Foods Market

Whole Foods Market is looking for a sharp, driven, and analytically minded Business Analyst II to join our Competitive Intelligence team. You will own end-to-end analyses that illuminate the competitive grocery landscape - translating retailer pricing, assortment, and performance data into strategic insights that directly shape our business. As the analytics go-to for competitive intelligence, you"ll turn complex competitive data into clear, decision-ready guidance.

This is a high-visibility role with real impact. The right candidate brings a strong foundation in retail merchandising, dives deep into complex pricing and assortment performance metrics, understands the business context behind the data, and continuously strives for deeper insight. As AI accelerates the pace of our work, you"ll help shape what"s next for competitive analytics - building scalable, self-serve reporting and leveraging emerging AI capabilities to accelerate time-to-insight.

This role goes beyond reporting: you"ll conduct deep-dive analyses on pricing, assortment, and competitive positioning, surfacing the "so what" behind the data. Partnering closely with Pricing & Merchandising leaders, you"ll develop strategy, launch case studies, and deliver clear, actionable findings - building repeatable analytical frameworks that improve the team"s speed and depth over time. We"re looking for someone who combines analytical depth with the ability to communicate clearly to senior stakeholders and who thrives on ownership and continuous improvement.

Competitive intelligence is a strategic priority at Whole Foods Market. You"ll have the opportunity to shape how we understand and respond to the competitive landscape, with the data, resources, and leadership support to make a real difference.

Skills

Strong ownership mindset - you dive deep, take accountability for your work, and earn trust through consistent delivery

Expert-level SQL (Redshift preferred) and BI tools (QuickSight, Tableau); R or Python a plus

Experience building scalable dashboards and self-serve reporting that drive adoption

Strong quantitative reasoning - comfortable with large, complex datasets and ambiguous questions

Excellent communication - able to distill complex analyses into crisp narratives for senior stakeholders

Proactive and curious - you track food, retail, market news, and natural-products trends, read popular and trade press widely, and experiment with new tools (including AI/ML)

A strong foundation in retail merchandising that lets you contextualize pricing and assortment data within broader market dynamics, operating at both the detail and strategic levels

Key job responsibilities

Own end-to-end competitive analyses - scope, design, execute, and communicate deep-dives on pricing, assortment, and competitive positioning that surface the "so what" behind the data

Gather retail pricing, assortment, promotion, and location data on competitors, leveraging third-party sources and primary research

Build scalable, self-serve reporting in QuickSight and Redshift SQL that lets stakeholders access competitive insights without analyst dependency

Serve as the analytics subject-matter expert and go-to resource for Global and Regional Merchandising teams in competitive situations

Analyze competitive data to inform strategy, highlight opportunities, and drive recommendations for pricing and assortment adjustments

Partner closely with Pricing & Merchandising leaders to develop strategy, launch case studies, and deliver actionable findings

Build repeatable, scalable analytical frameworks that improve the team"s speed and depth

Communicate results clearly to senior business leaders, translating complex data into concise narratives

Accelerate time-to-insight by leveraging emerging AI capabilities and automation

Contribute as a key analytical voice on the Competitive Intelligence team, sharing best practices with fellow analysts

A day in the life

You start your morning reviewing a competitor"s latest price moves, spotting a gap and opportunity. You inspect a dashboard you built for Merchandising that lets them slice competitive results without filing a request. Mid-morning, you dig into a vendor data feed to validate pricing coverage, then meet with a Merchandising leader to discuss their category"s competitive positioning. After lunch, you present findings to a Director-level audience, turning the "so what" into clear action items. You close the day exploring an AI-powered workflow that could halve your analysis time and refining a reusable framework for competitive deep-dives.