Sr. Data Engineer

Benefits and compensation

Salary: $141,336 - $184,400 per year.

McKesson offers a competitive Total Rewards package that may include annual bonus or long-term incentive opportunities.

This role supports analytics, AI, and business intelligence through scalable data solutions, ETL or ELT on Databricks, and data governance. It is a 100% telecommute position from a U.S. home office.

Responsibilities

• Support and lead the design, development, and ongoing maintenance of scalable, high-performance data solutions that enable analytics, AI, and business intelligence across the organization.
• Help capture and document technical requirements for data flows among diverse operational systems and the data warehouse, and support end-to-end ETL/ELT development using Apache Spark on Databricks.
• Contribute to data ingestion into data lakes and warehouses, implement Delta Lake to ensure transactional integrity, and assist in orchestrating both batch and streaming data pipelines.
• Collaborate with cross-functional technology teams to extract, transform, and load data from diverse sources, design and optimize data models, and maintain software applications aligned with business needs.
• Explore and integrate emerging AWS technologies to enhance data engineering capabilities, develop complex SQL queries for data validation and transformation, and manage Databricks workspaces, clusters, and jobs.
• Support data quality initiatives, ensure compliance with governance and security policies, and contribute to the development and operationalization of machine learning and generative AI applications.
• Troubleshoot production workflows, refactor legacy systems, participate in code reviews, and mentor junior engineers.
• Demonstrate a strong understanding of modern data architecture, a proactive approach to problem solving, and a commitment to building reliable, scalable, and innovative data solutions.
• 100% telecommuting from a home office anywhere in the United States is supported.

Requirements

• Bachelor’s Degree in Computer Science or a related field.
• Five years of experience in the job offered or a related occupation.
• Experience in data engineering with Databricks and AWS.
• Experience with Apache Spark, SQL, and Python or Scala.
• Experience with Delta Lake, Unity Catalog, and cloud data warehouses (e.g., Redshift).
• Experience with data modeling, ETL/ELT processes, and data governance.
• Experience with orchestration tools including GitLab or Bitbucket and CI/CD practices.
• Experience collaborating with cross-functional teams to deliver data solutions using Python and Databricks in Agile environments.
• Experience designing and optimizing scalable data pipelines with Python and Spark in Databricks.
• Experience developing modular, reusable components in Databricks notebooks and workflows.
• Experience implementing data validation frameworks to ensure pipeline accuracy and consistency.

Technologies we use

• Databricks
• Apache Spark
• AWS
• Delta Lake
• Unity Catalog
• Redshift
• SQL
• Python
• Scala
• GitLab
• Bitbucket
• CI/CD
• Databricks notebooks
• Databricks workflows

How to apply

To apply, please send resumes to [email protected]. Reference #: 002115.

Equal Employment Opportunity

McKesson provides equal employment opportunities to applicants and employees, without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, age, genetic information, or any other legally protected category. For additional information on McKesson’s full Equal Employment Opportunity policies, visit our Equal Employment Opportunity page. McKesson is committed to being an Equal Employment Opportunity Employer and offers opportunities to all job seekers including job seekers with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, please contact us by sending an email to (United States) [email protected] or (Canada) [email protected]. Resumes or CVs submitted to this email box will not be accepted.