Senior Business Intelligence & Automation Analyst

MCKESSON; Atlanta (GA); On-site; USD 110,000 - 160,000; Full time

Job summary

McKesson is seeking a Senior Business Intelligence Analyst to design and scale analytics, reporting, and value realization across the AIM28 program. The role is a hands-on contributor reporting to the Finance Lead, owning end-to-end data models, ETL pipelines, dashboards, and automated insights to support executives and program leaders.

The ideal candidate combines deep SQL, data modeling, BI visualization, automation, and AI-enabled analytics with strong business and finance acumen.

Job description

McKesson is an impact-driven, Fortune 10 company that touches virtually every aspect of healthcare. We are known for delivering insights, products, and services that make quality care more accessible and affordable. Here, we focus on the health, happiness, and well‑being of you and those we serve – we care.

What you do at McKesson matters. We foster a culture where you can grow, make an impact, and are empowered to bring new ideas. Together, we thrive as we shape the future of health for patients, our communities, and our people. If you want to be part of tomorrow’s health today, we want to hear from you.

The Senior Business Intelligence Analyst is a highly visible, hands‑on individual contributor responsible for building and scaling AIM28’s analytics, reporting, and value‑realization measurement capabilities. Reporting to the AIM28 Finance Lead, this role will design and own end‑to‑end data models, ETL pipelines, dashboards, and automation solutions that transform complex, fragmented data into trusted insights for executives and program leaders. In addition, this role will support other strategic projects as required.

The ideal candidate combines deep technical expertise in SQL, data modeling, BI visualization, automation, and AI‑enabled analytics with strong business and finance acumen. Operating as the sole analytics builder within the AIM28 Finance team, this person will create the program’s single source of truth for KPI, benefit, investment, and value‑realization reporting while driving self‑service analytics, reporting automation, and AI‑powered insights across the AIM28 portfolio.

The Senior Business Intelligence Analyst will lead the development of business intelligence, data visualization, analytics, and reporting automation for the AIM28 program and other strategic projects within U.S. Pharmaceutical Distribution (USPD). AIM28 is McKesson’s AI‑enabled transformation program, organized around a portfolio of Big Bets, each accountable for delivering measurable business outcomes. This role reports directly into the Sr. Director, Finance (AIM28). This role is the hands‑on builder who turns Big Bet data into trusted, automated benefit and value‑realization reporting for program leadership and senior executives. The source material varies: some data arrives raw and needs business logic before anyone can use it, some lives in manual files, and some is already visualized in dashboards the business teams built for themselves.

You will architect an AI‑ready analytics and reporting model that pairs traditional dashboards with AI capabilities such as automated narratives and conversational agents, so stakeholders can self‑serve and get to insight faster. Where data is raw, you will establish the transformation logic that makes it consumable. Where reporting lives in manual files or scattered dashboards, you will integrate and standardize it into Big Bet and AIM28 program‑level solutions. This is a highly visible individual contributor role. We are looking for a builder with deep SQL proficiency, strong knowledge of data design, and the visualization and storytelling skill to brief senior executives. Expect problems to show up half‑defined; your job is to turn them into reliable numbers and clear answers.

This role works under the direction of the AIM28 Finance Lead partnering with Big Bet teams, the transformation office, and McKesson Technology to codify KPI definitions and benefit methodologies into governed data models. The goal