This role pays less than
79%
of similar roles. Most pay
$159,000–$212,125
— the shaded band above.
At the midpoint, this role pays about
$152k
versus about
$186k
for comparable roles.
Based on 240 similar postings.
Employer
About McKesson Corporation
McKesson Corporation is a premier American healthcare services company that distributes pharmaceuticals, medical-surgical supplies, and provides technology to the healthcare industry.
McKesson Corporation currently has
61 open roles
on FindRole.
Listed pay typically runs
$121,100–$201,900
across 61 roles with salary data.
Manager, Data Analytics joins the Generics organization to bridge the gap between business operations and technical execution. This role focuses on modernizing legacy automations, migrating platforms, and building self-service analytics for pricing, finance, and manufacturer relations teams. The successful candidate will collaborate with stakeholders to identify manual pain points and translate them into clear requirements while developing production-ready solutions. Daily responsibilities include writing Python code for ETL processes and API integrations, designing dashboards in Power BI, Tableau, or Looker, and building data pipelines on cloud platforms like Snowflake or Databricks. The role also involves replacing RPA automations and identifying practical applications for AI and machine learning within reporting workflows. Candidates must possess strong SQL skills, a deep understanding of data modeling, and the ability to communicate complex technical concepts to non-technical business partners.
Power BI
Power Platform
Power Apps
Power Automate
Databricks
SQL
AI
Data Analytics
Data Engineering
KPI Reporting
Supply Chain Analytics
Automation
Data Pipelines
SQL
Power BI
Tableau
Python
Databricks
Microsoft Fabric
Azure Data Factory
Snowflake
ETL
ELT
Data Modeling
GenAI
LLM
Power Automate
Power Apps
Excel
S/4HANA
Agile
Power BI
Tableau
Python
SAS
Databricks
MS SQL
AWS
Azure
GCP
Machine Learning
Predictive Modeling
Data Visualization
Data Pipelines
Statistical Modeling
Exploratory Data Analysis
Data Integrity