Top Benefits
About the role
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 is a senior individual contributor within our Decision Intelligence organization. This pivotal role involves leading the design, development, and operational management of scalable data engineering and analytics solutions across the PSaS Business Unit. The successful candidate will serve as a technical leader and player coach, combining hands-on engineering expertise with strategic solution leadership, mentorship, and cross-functional influence. You will be responsible for driving end-to-end technical delivery of complex data initiatives, ensuring the creation of reliable, efficient, and scalable data pipelines that support advanced analytics and machine learning use cases.
This role requires collaboration with various stakeholders, including data architects, product managers, data scientists, and business analysts, to translate analytical requirements into innovative data solutions. The Lead Data Engineer will also play a key role in establishing and maintaining engineering standards, best practices, and architectural decisions aligned with McKesson’s enterprise data strategy. The position offers an opportunity to impact healthcare by enabling data-driven decision-making and operational excellence across the organization.
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 required, with a strong ability to independently lead complex technical initiatives with minimal oversight. Proven experience influencing technical direction and mentoring other engineers without formal management responsibilities is essential. Deep understanding of data architecture, ETL/ELT patterns, and large-scale data processing is necessary. Strong stakeholder communication and collaboration skills are also critical to success in this role.
Educational qualifications typically include a degree or equivalent in Computer Science, Data Science, or related fields. Hands-on experience with cloud platforms, automation, and infrastructure as code further enhances candidacy.
Responsibilities
Lead end-to-end technical delivery for complex data engineering initiatives or domains, ensuring solutions are scalable, reliable, and aligned with enterprise standards. Serve as a senior technical point of contact for data engineering within cross-functional squads, providing guidance and technical expertise. Design and build scalable, reliable batch and real-time data pipelines across internal and external systems, utilizing technologies such as Databricks, Snowflake, Azure Data Factory, and Kafka. Influence architectural decisions in collaboration with Data Architects and enterprise teams, ensuring solutions adhere to best practices and strategic goals. Define, implement, and uphold engineering standards, patterns, and practices to ensure high-quality data products. Mentor and coach data engineers through design reviews, code reviews, and technical development activities to foster a culture of continuous improvement. Ensure the quality, performance, and long-term maintainability of data pipelines and data products. Partner with Product Managers, Data Scientists, Analysts, and business stakeholders to translate analytical requirements into scalable, efficient data solutions. Promote automation and reusability across data engineering solutions to optimize efficiency and reduce technical debt. Oversee testing strategies, production readiness, observability, and operational stability of data pipelines to ensure seamless deployment and ongoing support. Identify and address technical debt proactively, leading remediation efforts to enhance system robustness. Support advanced analytics and machine learning initiatives through optimized data models and pipelines, enabling data science teams to deliver impactful insights. Communicate complex technical designs, tradeoffs, risks, and outcomes clearly to stakeholders at all levels of the organization.
Benefits
McKesson offers a comprehensive and competitive total rewards package designed to support our employees' well-being and professional growth. Benefits include health insurance, retirement plans, paid time off, and wellness programs. We also provide opportunities for continuous learning and development, including training, certifications, and career advancement programs. Our flexible work arrangements and supportive work environment foster a healthy work-life balance. Additionally, employees may be eligible for performance-based bonuses and long-term incentives, reflecting our commitment to recognizing and rewarding exceptional contributions.
Equal Opportunity
McKesson is an Equal Opportunity Employer. We are committed to providing equal employment opportunities to all 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. We value diversity and inclusion and strive to create a workplace where everyone feels respected and empowered. If you require a reasonable accommodation during the application process, please contact us via email. For more information about our policies, please visit our Equal Employment Opportunity page.
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Top Benefits
About the role
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 is a senior individual contributor within our Decision Intelligence organization. This pivotal role involves leading the design, development, and operational management of scalable data engineering and analytics solutions across the PSaS Business Unit. The successful candidate will serve as a technical leader and player coach, combining hands-on engineering expertise with strategic solution leadership, mentorship, and cross-functional influence. You will be responsible for driving end-to-end technical delivery of complex data initiatives, ensuring the creation of reliable, efficient, and scalable data pipelines that support advanced analytics and machine learning use cases.
This role requires collaboration with various stakeholders, including data architects, product managers, data scientists, and business analysts, to translate analytical requirements into innovative data solutions. The Lead Data Engineer will also play a key role in establishing and maintaining engineering standards, best practices, and architectural decisions aligned with McKesson’s enterprise data strategy. The position offers an opportunity to impact healthcare by enabling data-driven decision-making and operational excellence across the organization.
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 required, with a strong ability to independently lead complex technical initiatives with minimal oversight. Proven experience influencing technical direction and mentoring other engineers without formal management responsibilities is essential. Deep understanding of data architecture, ETL/ELT patterns, and large-scale data processing is necessary. Strong stakeholder communication and collaboration skills are also critical to success in this role.
Educational qualifications typically include a degree or equivalent in Computer Science, Data Science, or related fields. Hands-on experience with cloud platforms, automation, and infrastructure as code further enhances candidacy.
Responsibilities
Lead end-to-end technical delivery for complex data engineering initiatives or domains, ensuring solutions are scalable, reliable, and aligned with enterprise standards. Serve as a senior technical point of contact for data engineering within cross-functional squads, providing guidance and technical expertise. Design and build scalable, reliable batch and real-time data pipelines across internal and external systems, utilizing technologies such as Databricks, Snowflake, Azure Data Factory, and Kafka. Influence architectural decisions in collaboration with Data Architects and enterprise teams, ensuring solutions adhere to best practices and strategic goals. Define, implement, and uphold engineering standards, patterns, and practices to ensure high-quality data products. Mentor and coach data engineers through design reviews, code reviews, and technical development activities to foster a culture of continuous improvement. Ensure the quality, performance, and long-term maintainability of data pipelines and data products. Partner with Product Managers, Data Scientists, Analysts, and business stakeholders to translate analytical requirements into scalable, efficient data solutions. Promote automation and reusability across data engineering solutions to optimize efficiency and reduce technical debt. Oversee testing strategies, production readiness, observability, and operational stability of data pipelines to ensure seamless deployment and ongoing support. Identify and address technical debt proactively, leading remediation efforts to enhance system robustness. Support advanced analytics and machine learning initiatives through optimized data models and pipelines, enabling data science teams to deliver impactful insights. Communicate complex technical designs, tradeoffs, risks, and outcomes clearly to stakeholders at all levels of the organization.
Benefits
McKesson offers a comprehensive and competitive total rewards package designed to support our employees' well-being and professional growth. Benefits include health insurance, retirement plans, paid time off, and wellness programs. We also provide opportunities for continuous learning and development, including training, certifications, and career advancement programs. Our flexible work arrangements and supportive work environment foster a healthy work-life balance. Additionally, employees may be eligible for performance-based bonuses and long-term incentives, reflecting our commitment to recognizing and rewarding exceptional contributions.
Equal Opportunity
McKesson is an Equal Opportunity Employer. We are committed to providing equal employment opportunities to all 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. We value diversity and inclusion and strive to create a workplace where everyone feels respected and empowered. If you require a reasonable accommodation during the application process, please contact us via email. For more information about our policies, please visit our Equal Employment Opportunity page.