Job Description

Salary: $122,100 - 162,800 per year Requirements:

• We are looking for someone with recognized expertise in data engineering and analytics in large enterprise environments.
• You should be able to independently lead complex technical initiatives with minimal supervision.
• You need proven experience influencing technical direction and mentoring engineers without formal people management responsibility.
• You should have a strong grasp of data architecture, ETL/ELT patterns, and large-scale data processing.
• You need strong stakeholder communication and collaboration skills.
• You should be highly proficient in SQL, Python, and scripting.
• You need hands-on experience with Databricks, Snowflake, Azure Data Factory, Confluent Kafka or Azure Event Hub, PySpark, analytical SQL, Power BI and/or Tableau, Apache Airflow, dbt, and Alation.
• You should understand data modeling, metadata, lineage, and data quality practices.
• You need experience with cloud platforms, including SaaS, PaaS, and IaaS.
• You should have experience implementing automation and Infrastructure as Code.
• You should be able to support advanced analytics and ML enablement.
• We require a degree or equivalent and typically 10+ years of relevant experience.
• Preferred experience includes leading enterprise-scale or business-unit-wide data initiatives.
• Preferred experience includes exposure to real-time, event-driven data architectures.
• Preferred experience includes familiarity with data governance programs and stewardship responsibilities.
• Preferred experience includes experimentation with emerging data and AI technologies.
• Preferred experience includes work in highly regulated or complex business environments.

• We lead end-to-end technical delivery for complex data engineering initiatives or domains.
• We serve as a senior technical point of contact for data engineering within cross-functional squads.
• We design and build scalable, reliable batch and real-time data pipelines across internal and external systems.
• We lead solution design and help shape architectural decisions with Data Architects and enterprise teams.
• We define and maintain engineering standards, patterns, and best practices aligned with our enterprise data strategy.
• We mentor and guide data engineers through design reviews, code reviews, and technical coaching.
• We ensure the quality, reliability, performance, and long-term maintainability of our data products.
• We partner with Product Managers, Data Scientists, Analysts, and business stakeholders to turn analytical needs into scalable solutions.
• We promote an automation-first and reusability-focused approach across our data engineering work.
• We oversee testing strategies, production readiness, observability, and the operational stability of data pipelines.
• We proactively identify technical debt and lead remediation efforts.
• We enable advanced analytics and machine learning use cases through optimized data models and pipelines.
• We communicate technical designs, tradeoffs, risks, and results clearly to stakeholders.

• AI
• Airflow
• Azure
• Cloud
• Databricks
• ETL
• IaaS
• Support
• Kafka
• Machine Learning
• PaaS
• Power BI
• Python
• PySpark
• SQL
• Snowflake
• Tableau
• dbt

More:

We are McKesson, an impact-driven Fortune 10 healthcare company that delivers insights, products, and services designed to make quality care more accessible and affordable. Our culture encourages growth, impact, and new ideas as we shape the future of health for patients, communities, and our people. This Lead Data Engineer role sits within our Decision Intelligence organization and supports the PSaS Business Unit as a senior individual contributor and player-coach with strong technical leadership and cross-functional influence. We offer a competitive Total Rewards package, with a base pay range of $122,100 to $162,800, and may also provide bonus or long-term incentive opportunities.

last updated 37 week of 2026

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