About The Company
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.
About The Role
The Lead Data Engineer at McKesson plays a pivotal role within the Decision Intelligence organization. This senior individual contributor is responsible for leading the design, development, and operationalization of scalable data engineering and analytics solutions across the Pharmacy Services and Solutions (PSaS) Business Unit. The role combines technical expertise with leadership qualities, serving as a player-coach to guide and mentor a team of data engineers, influence architectural decisions, and collaborate with cross-functional teams. The ideal candidate will have a strong background in data architecture, large-scale data processing, and automation, enabling the organization to leverage data for strategic insights and advanced analytics.
This position offers an exciting opportunity to work on complex data initiatives, influence enterprise data strategies, and support innovative ML and analytics use cases. The Lead Data Engineer will serve as a technical authority, ensuring the delivery of high-quality, reliable, and maintainable data products that drive business value and support McKesson's mission to improve healthcare outcomes.
Qualifications
The ideal candidate will possess recognized expertise in data engineering and analytics within large enterprise environments. A minimum of 10+ years of relevant experience is typically required, along with a degree or equivalent qualification in Computer Science, Data Science, or related fields. Proven ability to independently lead complex technical initiatives with minimal oversight is essential. Candidates should demonstrate experience in influencing technical direction, mentoring engineers, and working collaboratively with diverse stakeholders. Deep understanding of data architecture, ETL/ELT patterns, and large-scale data processing is critical. Strong stakeholder communication and collaboration skills are also required to succeed in this role.
Technical proficiency in SQL, Python, scripting, and hands-on experience with tools such as Databricks, Snowflake, Azure Data Factory, Confluent Kafka, PySpark, Power BI, Tableau, Apache Airflow, dbt, and Alation are highly desirable. Knowledge of data modeling, metadata management, data lineage, and data quality practices is important. Experience with cloud platforms (SaaS, PaaS, IaaS), automation, Infrastructure as Code (IaC), and supporting advanced analytics and machine learning initiatives will set candidates apart.
Responsibilities
- Lead end-to-end technical delivery for complex data engineering initiatives, ensuring alignment with business goals and technical standards.
- Act as a senior technical point of contact within cross-functional squads, providing guidance and expertise on data engineering best practices.
- Design, develop, and maintain scalable, reliable batch and real-time data pipelines across internal and external systems.
- Collaborate with Data Architects and enterprise teams to influence and define architectural decisions and solution designs.
- Establish and uphold engineering standards, patterns, and best practices aligned with enterprise data strategy.
- Mentor and review work of data engineers, providing technical coaching, code reviews, and design feedback.
- Ensure data products are of high quality, reliable, performant, and maintainable over the long term.
- Partner with Product Managers, Data Scientists, Analysts, and business stakeholders to translate analytical requirements into scalable data solutions.
- Promote automation and reusability in data engineering solutions to improve efficiency and consistency.
- Oversee testing, production readiness, observability, and operational stability of data pipelines.
- Proactively identify technical debt and lead efforts to remediate issues, enhancing system robustness.
- Support advanced analytics and machine learning initiatives by optimizing data models and pipelines for ML workloads.
- Communicate technical designs, trade-offs, risks, and outcomes effectively to non-technical stakeholders.
Benefits
McKesson offers a competitive total rewards package, including base salary, annual bonuses, and long-term incentives based on performance, experience, and skills. Our comprehensive benefits program includes health, dental, vision insurance, retirement plans, paid time off, and wellness resources. We are committed to fostering a supportive work environment that promotes growth, development, and work-life balance. Additional perks may include flexible work arrangements, professional development opportunities, and employee assistance programs. Our goal is to create a workplace where employees feel valued, empowered, and motivated to contribute to our mission of improving healthcare.
Equal Opportunity
McKesson is an Equal Opportunity Employer that values diversity and inclusion in the workplace. We provide equal employment opportunities to all applicants and employees regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, age, genetic information, or any other legally protected category. We are committed to creating an inclusive environment where everyone can thrive. If you require a reasonable accommodation during the application process, please contact us via
