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McKesson · 17 hours ago

Principal Data Modernization Engineer

United States

Full-time

Remote

Lead/Staff

$179K/yr - $298K/yr

13+ years exp

McKesson is an impact-driven, Fortune 10 company that touches virtually every aspect of healthcare. The Principal Data Modernization Engineer provides trusted technical leadership across data modernization efforts, ensuring initiatives are cohesive and aligned with long-term strategy while partnering closely with analytics teams.

BiopharmaBiotechnologyHealth CareInformation TechnologyPharmaceutical

No H1B

Responsibilities

Act as the Senior Director’s technical delegate for data modernization, providing trusted technical guidance across Data Technology

Guide and shape high-impact modernization decisions that span multiple teams or domains

Provide clarity and direction in complex or ambiguous modernization scenarios, enabling leaders and teams to move forward with confidence

Ensure key technical decisions are clearly articulated, shared, and consistently applied across Data Tech

Proactively identify gaps, inefficiencies, or unclear ownership in data modernization (e.g., ingestion ownership, platform responsibilities, data flow boundaries)

Develop a strong understanding of current-state systems, constraints, and dependencies across teams

Translate ambiguity into clear problem statements, decision options, and technical recommendations

Partner with Engineering and Architecture Directors to align on modernization approaches and technical direction

Bring together the appropriate leaders and senior engineers to explore options, assess trade-offs, and align on paths forward

Foster constructive, outcome-focused discussions that balance technical rigor with practical delivery considerations

Partner with analytics teams to understand analytical usage patterns, performance needs, and downstream considerations that should inform data platform and modernization decisions

Ensure data modernization decisions appropriately support analytics scalability, usability, and long-term analytical flexibility

Guide the application of data modernization patterns and approaches across transactional, analytical, platform, and modeling work, with consideration for downstream analytical consumption and performance needs

Help teams consistently interpret and apply data architecture standards in real-world modernization scenarios

Identify opportunities to simplify, standardize, or improve how modernization patterns are used across Data Tech

Maintain visibility into emerging modernization risks, architectural drift, or areas of growing technical debt

Surface insights and recommendations to leadership early, supporting informed decision-making

Help reduce reliance on informal heroics by promoting clear, repeatable approaches to technical decision-making

Qualification

Data engineeringCloud-based data platformsData modelingData ingestion patternsAnalytics collaborationTechnical communicationFacilitation skills

Required

Bachelor's degree in Computer Science, Information Systems, or equivalent experience and typically requires 13+ years of relative experience in data engineering, data platforms or large-scale systems

Experience partnering with analytics or reporting teams to ensure data platforms, models and pipelines effectively support analytical workloads and evolving analytical needs

Strong Technical understanding of: Transactional and analytical data systems, Data ingestion, integration, and synchronization patterns, Cloud-based data platforms, specifically Databricks, Data modeling and domain-oriented data design

Demonstrated ability to influence technical direction through credibility, collaboration and clear communication

Experience working effectively in complex, multi-team technical environments