Data Management Analyst

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.

This role sits at the center of BSMR’s transformation into a modern data and AI-driven organization. The position will support Brand Sourcing & Manufacturer Relations (BSMR) by delivering trusted, enterprise grade analytics and reporting while actively participating in the evolution of a centralized Databricks based data platform and the expansion of advanced analytics, AI, and Agentic AI capabilities. As BSMR Analytics & Insights continues to consolidate fragmented data sources into a governed, scalable platform, this role offers a unique opportunity to grow alongside the team’s technical and analytical maturity—from foundational reporting and reconciliation today, to increasingly automated, intelligent, and agent enabled analytics in the future.

This is an ideal role for a data professional who wants to build a deep business context, gain hands‑on experience with modern analytics platforms, and grow into more advanced analytics and AI enabled use cases as the platform and team evolves.

The role is responsible for delivering high‑quality analytics and reporting solutions across the end‑to‑end manufacturer and logistics lifecycle, enabling BSMR leadership and stakeholders to make informed, defensible decisions. The position partners closely with business, IT, and data platform teams to ensure analytics are accurate, auditable, scalable, and aligned to enterprise standards, quality analytics and reporting solutions across the end‑to‑end manufacturer and logistics lifecycle.

• Lead end‑to‑end delivery of enterprise reporting and analytics solutions supporting Brand Sourcing & Manufacturer Relations (BSMR), spanning sales, chargebacks, purchasing, inventory, and manufacturer performance data.
• Support the migration and centralization of analytics from disparate sources into the BSMR Databricks platform, partnering with platform and engineering teams to align reporting with governed data models.
• Perform source‑to‑target reconciliation, data validation, and issue resolution to ensure accuracy, consistency, and auditability across SAP and other data sources.
• Proactively identify data quality gaps, inconsistencies, and enhancement opportunities, driving remediation through structured issue tracking, root cause analysis, and stakeholder collaboration.
• Serve as a trusted analytics partner to BSMR leadership, IT, and business stakeholders, clearly communicating data readiness, risks, timelines, and dependencies.
• Design, develop, and maintain enterprise reporting repositories that support ongoing operational needs and future analytical use cases.
• Identify and evaluate opportunities for automation and analytical advancement, contributing to the team’s roadmap for scalable analytics, AI‑enabled insights, and agent‑driven capabilities.
• Support ad‑hoc and exploratory analytics while helping transition recurring requests into standardized, automated solutions.

Degree or equivalent and typically requires 4+ years of relevant experience.

Bachelor’s degree in computer science, business or other related field or 4+ years of experience in data analytics.

This role provides hands‑on exposure to:

• A modern Databricks analytics platform serving as the foundation for enterprise reporting and advanced analytics.
• The evolution from traditional BI to AI assisted and Agentic AI enabled analytics, as the BSMR Analytics & Insights team expands its capabilities.
• Cross‑functional collaboration with business, data engineering, data science, and technology…