Data Analytics Engineer

McKesson • Alpharetta, GA

16h • Hybrid

About The Position

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 offers location flexibility and is open to candidates across the United States. Candidates based in the Dallas–Fort Worth (DFW) area will be hired in a hybrid capacity and are expected to work onsite at our headquarters in Irving, TX a minimum of two (2) days per week, with the remaining days worked remotely. Specific in‑office days may be designated based on team needs and business priorities. Current Need: As a Data Analytics Engineer, you will play a pivotal role in designing, implementing and owning data solutions for US Oncology data sets. This role requires extensive technical knowledge to manage complex tasks in Databricks, building tools with Python, leveraging API systems and assisting in the management of internal data and data-related systems. This role will include additional activities such as analyzing data, designing solutions, providing direct analytical support to stakeholders, architecting data systems, and development of scalable solutions that support business goals.

Requirements

• 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

Responsibilities

• Design and Architecture: Develop and maintain areas including data models, data pipelines, and technical specifications to support business goals and analytics initiatives.
• Database Management: Leverage cloud systems such as Databricks for data processing, analytics, and machine learning tasks, ensuring optimal performance and cost efficiency.
• Data Integration: Design and implement processes for data integration within a medallion architecture to ensure seamless data flow across various systems.
• Performance Optimization: Continuously monitor and optimize data processes, ensuring high performance, reliability, and scalability.
• Data Strategy: participate in setting comprehensive data strategy goals for the team in alignment with business needs.
• Collaboration: 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.
• Innovation: Stay current with emerging technologies and industry trends and recommend innovative solutions to enhance our data architecture.
• Technical Project Management: Drive technical projects forward by partnering with 2nd- and 3rd-party partners, including other internal McKesson teams.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed