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 is a senior individual contributor within McKesson's 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 deep hands-on engineering expertise with solution leadership, mentorship, and cross-functional influence.

As a technical leader, you will oversee end-to-end data pipeline development, influence architectural decisions, and ensure the delivery of high-quality, reliable data products that support advanced analytics and machine learning initiatives.

You will collaborate closely with product managers, data scientists, analysts, and business stakeholders to translate analytical requirements into scalable, efficient solutions. Your expertise will drive automation, reusability, and operational stability across data engineering initiatives, ensuring that data pipelines are optimized for performance, reliability, and long-term maintainability. This role offers a unique opportunity to shape the data architecture and influence the strategic direction of McKesson’s data ecosystem.

Qualifications The ideal candidate will have recognized expertise in data engineering and analytics within large, enterprise environments. A minimum of 10+ years of relevant experience, along with a degree or equivalent, is typically required.





Proven ability to independently lead complex technical initiatives with minimal oversight is essential, as is experience influencing technical direction and mentoring other engineers without formal management responsibilities. A deep understanding of data architecture, ETL/ELT patterns, and large-scale data processing is crucial, along with strong stakeholder communication and collaboration skills.

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 is required. Familiarity with data modeling, metadata, lineage, data quality practices, and cloud platforms (SaaS, PaaS, IaaS) is also necessary.

Experience supporting advanced analytics and machine learning enablement, along with automation and Infrastructure as Code (IaC), will be highly valued.

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 build scalable, reliable batch and real-time data pipelines across internal and external systems.
- Collaborate with Data Architects and enterprise teams to influence architectural decisions and define best practices.
- Establish and uphold engineering standards, patterns, and best practices aligned with enterprise data strategy.
- Mentor and guide data engineers through design reviews, code reviews, and technical coaching to foster a high-performing team.
- Ensure data products meet quality, reliability, performance,



and maintainability standards.
- Partner with Product Managers, Data Scientists, Analysts, and business stakeholders to translate analytical requirements into scalable solutions.
- Promote automation and reusability in data engineering solutions to optimize efficiency and consistency.
- Oversee testing strategies, production readiness, observability, and operational stability of data pipelines.
- Proactively identify technical debt and lead efforts to remediate issues and improve system robustness.
- Enable advanced analytics and machine learning use cases through optimized data models and pipelines.
- Communicate technical designs, tradeoffs, risks, and outcomes clearly to stakeholders at all levels.

Benefits McKesson offers a competitive compensation package as part of our Total Rewards program. Compensation is determined based on factors such as performance, experience, skills, equity, market evaluations, and geographical location. In addition to base salary, employees may be eligible for annual bonuses, long-term incentives, and other benefits. Our comprehensive benefits package includes health insurance, retirement plans, paid time off, and wellness programs designed to support your overall well-being. We are committed to fostering a positive, inclusive work environment that promotes professional growth and work-life balance.

Equal Prospect

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 dedicated to creating an inclusive environment where all individuals can thrive.

If you require a reasonable accommodation during the application process, please contact us via the provided channels. We value diversity and are committed to fostering a workplace that reflects the communities we serve.

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