Lead Analytics & Automation Engineer

McKesson•Atlanta, GA

1d•$114,200 - $190,400•Hybrid

About The Position

The Lead Analytics & Automation Engineer will lead requirements gathering, solution design, and adoption for self-service analytics and automation across the Generics organization. This role is critical to advancing McKesson's AIM28 initiative, including modernizing legacy RPA automations into scalable, AI-enabled solutions, SAP S4 Migration, and clearing the existing backlog of reporting and automation requests across pricing, finance, and manufacturer relations. Success requires strong business acumen and close partnership with data engineering, BI developers, and IT to ensure solutions are scalable, compliant, and aligned with enterprise data standards.

Requirements

Degree or equivalent and typically requires 7+ years of relevant experience.
Bachelor's or master's degree in Business, Finance, Economics, Information Systems, Computer Science, Data Analytics, or a related field
7+ years of experience in business analysis, analytics, or business intelligence, with at least 2 years in a leadership or mentorship role
Proven experience translating business requirements into reporting and analytics solutions
Proficiency in SQL and hands-on experience building dashboards in Power BI, Tableau, or Looker
Hands-on experience writing production-quality Python code (scripting, ETL/ELT, API integration); experience with RPA-to-AI/automation migration is a plus
Experience delivering analytics solutions in a modern data environment (e.g., Snowflake, Databricks, or comparable cloud platforms)
Strong understanding of BI best practices, data modeling, and end-to-end analytics delivery from requirements through UAT and adoption

Nice To Haves

Proficiency in Python for automation and AI solution development, including backend components of automation and analytics solutions
Working knowledge of data modeling concepts and data governance/compliance principles, plus familiarity with AI/ML concepts (predictive analytics, GenAI, process automation) sufficient to scope use cases for technical teams
Self-starter mentality with strong organizational skills, attention to detail, and the ability to manage multiple concurrent projects in a fast-paced, regulated business environment
Strong analytical and problem-solving skills, with the ability to translate ambiguous business problems into clear requirements and technical specifications
Excellent communication and stakeholder management skills, with the ability to lead requirements-gathering sessions and align cross-functional partners without direct authority

Responsibilities

Develop intuitive, self-service dashboards and analytics solutions for the Generics organization, enabling stakeholders to monitor performance, track KPIs, and make informed decisions
Lead the identification and implementation of automation opportunities across reporting and business workflows, including modernizing legacy RPA automations into scalable, AI-enabled solutions, aligned to McKesson's AIM28 initiative
Drive resolution of the existing analytics and automation backlog by prioritizing requests based on business impact, effort, and strategic alignment
Support execution of the BI team's AI strategy by identifying high-impact use cases and partnering with technical teams to embed AI/ML capabilities into analytics solutions
Design and deliver scalable reporting and data products supporting pricing, finance, and manufacturer relations, translating stakeholder priorities into actionable requirements
Drive end-to-end analytics delivery, including requirements gathering, solution design, UAT, and adoption, in collaboration with data engineering, BI developers, and IT to ensure solutions meet enterprise data standards
Support the upcoming SAP S4 and Databricks migrations by identifying impacted reporting and analytics solutions, and updating downstream dashboards, data products, and workflows to ensure continuity through both transitions
Contribute to knowledge sharing and best practices, providing backup support and mentorship across the analytics team as needed