Whole Foods Market is looking for a Business Analyst to join our Promotion Analytics team. In this role, you will own end-to-end analyses that drive promotional strategy, serving as the analytics go-to for your business area. You will independently translate complex business questions into actionable insights, build scalable self-serve reporting frameworks, and influence decisions across merchandising, marketing, and category teams. You will partner within the Promotions Analytics team to increase the speed from data analysis to insight—leveraging emerging AI capabilities to unlock new areas of value for the business.

This role goes beyond reporting: you will design measurement approaches, identify opportunities proactively, and drive recommendations that shape how Whole Foods Market evaluates and optimizes promotional programs. We are looking for someone who combines analytical depth with the ability to communicate clearly to senior stakeholders and who thrives in an environment of ownership and continuous improvement.

Skills:
- Strong ownership mindset — you dive deep into the data, take accountability for the quality and impact of your work, and earn trust through consistent delivery

- Expert-level proficiency in SQL (Redshift preferred) and business intelligence tools (e.g., QuickSight, Tableau)

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

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

- Excellent written and verbal communication — able to distill complex analyses into crisp narratives for senior stakeholders

- Proactive and curious — you stay ahead of industry trends, experiment with new tools (including AI/ML capabilities), and continuously improve how the team works

- Strong organizational skills with ability to manage multiple concurrent workstreams and prioritize effectively

Key job responsibilities
- Own end-to-end promotional analytics — independently scope, design, execute, and communicate analyses that inform merchandising strategy and campaign optimization

- Build scalable, self-serve reporting frameworks in QuickSight and Redshift SQL that enable stakeholders to access insights without analyst dependency

- Serve as the analytics subject-matter expert for your business area, proactively identifying trends, risks, and opportunities in promotional performance data

- Drive recommendations to senior leadership — translate findings into clear, actionable recommendations that influence promotional strategy and investment decisions

- Accelerate time-to-insight by leveraging emerging AI capabilities and automation to streamline data workflows and expand analytics coverage into new areas of the business

- Analyze market, competitor, behavioral, and transactional data to evaluate promotional effectiveness, customer engagement, and shopping behavior

- Design and refine measurement approaches — develop frameworks for evaluating promotional ROI, incrementality, and program performance

- Provide technical guidance to peers — mentor junior analysts and contribute to team best practices for data modeling, visualization, and analytical rigor

- Partner cross-functionally with Program Managers, Category Merchandising, and Marketing to align analytics with business objectives and planning cycles

- Lead insights reviews — synthesize findings, present to Director+ audiences, and provide forward-looking recommendations that inform planning

A day in the life
You start your morning reviewing recent promotional performance data, quickly identifying an emerging trend in regional response rates. You update a QuickSight dashboard you built for the merchandising team—one that lets them slice results without filing an analytics request. Mid-morning, you meet with your Program Manager to align on the measurement approach for an upcoming national campaign, proposing an incrementality framework you've been developing. After lunch, you present quarterly promotional insights to a Director-level audience, fielding questions and turning feedback into follow-up action items. In the afternoon, you explore a new AI-powered workflow that could cut your segmentation analysis time in half, documenting your findings for the broader team. You close the day mentoring a fellow analyst on a tricky SQL optimization and reviewing a pull request for a shared reporting template.