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 the Decision Intelligence organization, responsible for leading the design, delivery, and operationalization of scalable data engineering and analytics solutions across the PSaS Business Unit. This role combines technical expertise with leadership qualities, serving as a technical leader and player coach. The position requires hands-on engineering skills, solution architecture, mentorship, and cross-functional influence to ensure the successful implementation of data initiatives that drive business insights and operational efficiencies.

The ideal candidate will lead end-to-end technical delivery for complex data engineering projects, design scalable data pipelines, and influence architectural decisions in collaboration with data architects and enterprise teams. They will also mentor data engineers, uphold engineering standards, and partner with product managers, data scientists, and business stakeholders to translate analytical requirements into robust, scalable solutions. The role emphasizes automation, operational stability, data quality, and enabling advanced analytics and machine learning use cases.

Qualifications The successful candidate should demonstrate recognized expertise in data engineering and analytics within large, enterprise environments. A minimum of 10+ years of relevant experience and a degree or equivalent qualification are typically required.



They should possess a strong ability to independently lead complex technical initiatives with minimal oversight and influence the technical direction of data engineering teams without formal management responsibilities.

Deep understanding of data architecture, ETL/ELT patterns, and large-scale data processing is essential, along with excellent stakeholder communication and collaboration skills. Technical proficiency in SQL, Python, scripting, and experience with cloud-based data platforms and tools are mandatory. The candidate should also have experience with data modeling, metadata management, data lineage, and data quality practices.

Familiarity with automation, Infrastructure as Code (IaC), and advanced analytics or machine learning enablement is highly desirable.

Responsibilities Lead end-to-end technical delivery for complex data engineering initiatives or domains, ensuring timely and high-quality outputs.

Serve as a senior technical point of contact for data engineering within cross-functional squads, providing guidance and expertise.

Design and develop scalable, reliable batch and real-time data pipelines across internal and external systems, ensuring data integrity and performance.

Collaborate with Data Architects and enterprise teams to influence architectural decisions and design solutions aligned with enterprise standards.

Define and enforce engineering standards, best practices, and patterns to maintain consistency and quality across data products.

Mentor and review the work of data engineers, providing technical coaching, code reviews, and design feedback.

Ensure the quality, reliability, and operational stability of data pipelines, including testing strategies, monitoring, and observability practices.

Partner with product managers, data scientists, analysts,



and business stakeholders to translate analytical requirements into scalable data solutions.

Promote an automation-first approach and focus on reusability to enhance efficiency and maintainability of data engineering solutions.

Identify and address technical debt proactively, leading remediation efforts to improve system health.

Support advanced analytics and machine learning initiatives through optimized data models and pipelines.

Communicate technical designs, tradeoffs, risks, and outcomes effectively to both technical and non-technical stakeholders.

Perks McKesson offers a competitive total rewards package that includes base salary, performance-based bonuses, and long-term incentive opportunities. Our comprehensive benefits program encompasses health, dental, and vision insurance, retirement plans, paid time off, and wellness programs. We are committed to supporting your professional growth through continuous learning opportunities, leadership development, and a collaborative work environment.

Additionally, employees have access to flexible work arrangements, employee assistance programs, and resources aimed at promoting work-life balance. Our benefits are designed to empower you to thrive both professionally and personally, ensuring you have the support needed to succeed in your role and beyond.

Equal Opportunity McKesson is an Equal Opportunity Employer. We provide 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. We are committed to fostering an inclusive environment where everyone can thrive and contribute to our mission.

If you require a reasonable accommodation during the application process, please contact us by email. Resumes or CVs submitted to email addresses or through unofficial channels will not be accepted. We encourage diverse candidates to apply and look forward to welcoming talented individuals to our team.

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