Lead Data Engineer

**Lead Data Engineer** ---------------------- Remote \- Virginia **Job ID** JR0147056 **Category** Database Engineering **Post Date** Jun. 04, 2026 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. **Job Title** ------------- Lead Data Engineer (Operations / KTLO) **Summary** ----------- We are seeking a technically strong and operationally focused Lead Data Engineer to manage the day\-to\-day operations of PSaS Data \& Analytics platforms. This role focuses on Keep the Lights On (KTLO) activities, ensuring reliable platform performance, SLA adherence, and continuous improvement across data systems. ### **What You’ll Do** * Own and manage day\-to\-day operations of Data \& Analytics platforms, ensuring SLA\-driven support and service delivery * Support cross\-functional teams by delivering data insights for complex business problems * Collaborate with data engineers, data scientists, and stakeholders to deliver data\-driven outcomes * Gather requirements, define data models, and support solution design with architects and engineering teams * Perform data exploration, analysis, and maintain data definitions, business rules, and lineage * Drive documentation, testing (functional, regression, exploratory), and execution of test plans * Build, enhance, and support scalable data pipelines (batch and real\-time) across multiple systems * Implement data governance practices and promote data literacy across the organization * Identify and address technical debt; continuously improve and optimize processes * Monitor, troubleshoot, and tune performance of data platforms and analytical solutions * Champion automation\-first, enterprise\-first, and reusable solution design principles * Support infrastructure and cloud\-based solutions including SaaS, PaaS, IaaS, and IaC practices * Communicate insights and results through reporting and presentations ### **What You Bring** * Strong experience with modern data platforms including Databricks, Snowflake, and Azure Data Factory * Proficiency in SQL, Python, and/or R for data analysis and engineering * Experience with reporting and visualization tools such as Power BI * Knowledge of legacy and enterprise systems such as SAP, SQL Server, DataStage, and Unix scripting * Strong understanding of data engineering, analytics, and large\-scale data processing * Experience with distributed data processing tools (e.g., PySpark) * Familiarity with too