Lead Data Architect & Engineer

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 tomorrows health today we want to hear from you.

Role Summary

The Lead Data Engineer / Architect is a senior individual contributor on McKessons Provider Revenue Operations team. This role owns the data architecture pipelines models and automation behind revenue and performance analytics.

The role builds and supports the data used for sales performance dashboards month-end and quarter-end close payment and commission validation and leadership reporting. It works closely with technical teams business partners and leaders to deliver scalable solutions that meet current needs and support future growth.

This person serves as the primary technical lead for Revenue Operations data architecture and development including cloud platforms system integrations automation and platform migrations.

Much of this work currently depends on manual processes and individual knowledge. This role will replace those dependencies with automated reusable data infrastructure so that reporting is accurate consistent and independent of any one person.

An AI-minded approach is core to the role. Modern AI capabilities such as retrieval-augmented generation (RAG) large language models and agentic workflows are applied where they measurably speed up or sharpen revenue intelligence along with building the data foundations that make those use cases possible. AI is a tool this work relies on when it fits not the primary mandate.

This position is open to applicants located anywhere in the United States. Compensation will vary based on the selected candidates geographic location.

Key Responsibilities

Revenue and Performance Data Architecture

• Design build and support a cloud-based data environment for structured semi-structured and unstructured revenue and performance data.

• Define Revenue Operations data architecture and cloud data models based on business analytical operational security and regulatory needs.

• Own the full data lifecycle from data collection and transformation through dashboards and reports.

• Automate the data flows supporting month-end and quarter-end close.

• Build consistent logic for payment commission quota and attainment validation.

• Develop conceptual logical and physical data models for operational and analytical use.

• Design ETL and ELT pipelines APIs real-time integrations and event-driven solutions.

• Integrate data from Salesforce Outreach finance systems and other business platforms.

• Build fact tables dimensions and semantic layers that provide a governed source of truth for Power BI and Tableau.

• Ensure every data product is accurate reliable scalable and maintainable.

Architecture Standards and Technical Direction

• Serve as the primary technical and architecture contact for revenue and performance analytics.

• Define standards for data integration backend frontend and automation solutions.

• Establish design patterns for cloud on-premises and hybrid environments.

• Maintain clear documentation showing how data is stored processed integrated secured and accessed.

• Evaluate and recommend technologies that improve development automation data management performance and support.

• Promote automation consistency and reuse across analytics and financial close processes.

Applied AI for Revenue Intelligence

• Build governed data foundations that allow revenue and performance data to be used safely by AI solutions including RAG pipelines.

• Apply large language models vector search and agentic workflows to practical Revenue Operations needs when they deliver measurable value.

• Develop use cases such as natural-language data queries automated variance explanations anomaly detection and self-service insights.

• Apply responsible AI standards including grounding guardrails privacy security and auditability.

Minimum Requirement

Degree or equivalent and typically requires 7 years of relevant experience.

Education

Bachelors degree or an equivalent combination of education and experience.

Critical Skills

• Typically requires 7 years of experience in data engineering analytics engineering or data and application architecture. Relevant advanced education may offset some experience.

• Expert knowledge of enterprise data pipelines ETL and ELT processes and data models supporting sales revenue or financial reporting.

• Advanced SQL Python and scripting skills for complex queries performance optimization and large-scale data processing.

• Deep knowledge of conceptual logical and physical data modeling including metadata lineage and enterprise data standards.

• Strong hands-on experience with Databricks Snowflake and Azure Data Factory.

Additional Skills

• Experience integrating Salesforce sales engagement platforms such as Outreach finance systems and other enterprise applications.

• Experience designing APIs real-time integrations and event-driven solutions.

• Experience building bots system integrations and reusable automation components.

• Hands-on experience with PySpark and Power BI or Tableau.

• Experience with cloud on-premises and hybrid platforms including SaaS PaaS IaaS and Infrastructure as Code.

• Experience building data architecture for sales performance revenue commission or incentive reporting.

• Experience supporting month-end or quarter-end close and financial or revenue reconciliation is strongly preferred.

• Ability to independently lead complex data and architecture initiatives with minimal oversight.

• Ability to explain technical work and recommendations clearly to sales and operations leaders.

• Experience with process automation enterprise applications or platform migrations is preferred.

• Experience applying emerging data and AI technologies to business problems is preferred.

• Experience in healthcare or another regulated industry is strongly preferred.

Physical Requirements

• General office demands.

• Must have the ability to travel up to20% of the time.

This position offers the possibility of a hybrid work arrangement based on recent updates to our in-office/workfromhome model. If located in DFW area the selected candidate may be expected to work onsite at our Las Colinas office a minimum of two (2) days per week with the remaining days worked remotely. Specific inoffice days may be designated according to team needs and business priorities.

We are proud to offer a competitive compensation package at McKesson as part of our Total Rewards. This is determined by several factors including performance experience and skills equity regular job market evaluations and geographical markets. The pay range shown below is aligned with McKessons pay philosophy and pay will always be compliant with any applicable regulations. In addition to base pay other compensation such as an annual bonus or long-term incentive opportunities may be offered. For more information regarding benefits at McKesson pleaseclick here.

Our Base Pay Range for this position

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McKesson is an Equal Opportunity Employer

McKesson provides 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. For additional information on McKessons full Equal Employment Opportunity policies visit our Equal Employment Opportunity page.

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