Data Analytics Engineer

McKesson is an impact-driven, Fortune 10 company that touches virtually every aspect of healthcare. As a Data Analytics Engineer, you will design, implement, and own data solutions for US Oncology data sets, requiring extensive technical knowledge to manage complex tasks and provide analytical support to stakeholders.

Responsibilities:

• Develop and maintain areas including data models, data pipelines, and technical specifications to support business goals and analytics initiatives
• Leverage cloud systems such as Databricks for data processing, analytics, and machine learning tasks, ensuring optimal performance and cost efficiency
• Design and implement processes for data integration within a medallion architecture to ensure seamless data flow across various systems
• Continuously monitor and optimize data processes, ensuring high performance, reliability, and scalability
• Participate in setting comprehensive data strategy goals for the team in alignment with business needs
• Work closely with data engineers, stakeholders, and business partners to understand and/or communicate project requirements. Help influence projects to drive the best results related to data quality, architecture and management
• Stay current with emerging technologies and industry trends and recommend innovative solutions to enhance our data architecture
• Drive technical projects forward by partnering with 2nd- and 3rd-party partners, including other internal McKesson teams

Requirements:

• Degree or equivalent and typically requires 4+ years of relevant experience
• 4+ years of experience in data engineering, software development, computer science or related field
• 3+ years' experience in database development with Snowflake or Databricks preferred
• 3+ years' experience with application development with Python preferred
• Healthcare experience a plus
• Experience with data modeling, database design, and data warehousing
• Ability to communicate complex concepts to non-technical stakeholders
• Understanding of data governance, data security, and data quality best practices
• Must be comfortable and proficient working with large and/or complex databases
• Working knowledge with project management tools like Jira, Asana
• Strong knowledge of cloud platforms with Azure preferred
• Knowledge of data visualization tools such as Power BI, Tableau, or Looker