Director Data Engineering

McKesson•Irving, TX

About The Position

McKesson is seeking an exceptional Director of Data Engineering to join McKesson Technology US Pharmaceutical Distribution (USPD) Decision Intelligence organization and lead the execution of design, development, and optimization of USPD data products. This role involves setting the technical vision, managing high-performing teams, and aligning data strategy with business objectives while managing large-scale data products built on modern data stack. This role involves collaborating with stakeholders to align data capabilities with business objectives and overseeing data governance, security, and best practices. The successful candidate will combine deep technical expertise with proven leadership capabilities to deliver high-impact data solutions that power critical business decisions across our USPD portfolio.

Requirements

12+ years experience of professional experience in related IT field with 4+ years experience in leadership, planning and communication roles.
Deep expertise in Microsoft Azure data services ecosystem (Azure Data Factory, Synapse Analytics, Data Lake Storage, Event Hubs, Cosmos DB)
Advanced proficiency with Databricks platform and advanced analytics workflows
Extensive experience with BI development, administration, and enterprise deployment
Strong foundation in modern data architectures, scalable Lakehouse using Medallion patterns and Unity Catalog; "RAG-ready" infrastructures and AI-driven data observability to automate quality and drift detection, real-time streaming, and event-driven systems
Proficiency in multiple programming languages (Python, Scala, SQL, .NET) and infrastructure
Strong technical aptitude and experience with a wide variety of technologies
Ability to rapidly learn and if required evaluate a new tool or technology
Strong verbal & written communication skills
Demonstrated technical leadership experience
Be an innovative thinker
Must have a strong customer and quality focus
Have been successful in working across organizational boundaries, bringing together people with diverse perspectives and experience to find solutions to complex technical issues
Proven experience in architecting AI-First Data Platforms , leveraging Generative AI to automate data curation workflows and implementing RAG-ready architectures that serve both structured BI and unstructured LLM applications.

Nice To Haves

Azure certifications (Azure Data Engineer Associate, Azure Solutions Architect Expert)
Databricks certifications (Professional Data Engineer, Professional ML Practitioner)
Experience in regulated industries (healthcare, financial services, manufacturing)

Responsibilities

Partner with executives, business leaders, and technology stakeholders to define data architecture vision and roadmap
Drive innovation in data engineering practices, emerging technologies, and platform capabilities to maintain competitive advantage
Establish data engineering standards, best practices, and governance frameworks across the organization
Design, build, and maintain scalable and AI-ready data products leveraging Microsoft Azure ecosystem, ensuring efficient data ingestion, transformation, and storage.
Lead advanced implementation of Databricks for large-scale data processing, machine learning workflows, and real-time analytics
Build, mentor, and lead a high-performing team of Data Engineering Directors, and technical specialists
Collaborate cross-functionally with Operations, Data Science, Analytics, IT, and Business Intelligence teams to deliver integrated solutions
Establish talent development programs, technical career progression paths, and engineering excellence initiatives
Foster culture of innovation, continuous learning, and technical excellence within the data engineering organization
Lead delivery of USPD data engineering products development in alignment with USPD DI Operations uptime, optimal performance, and cost efficiency
Implement comprehensive monitoring, alerting, and incident response capabilities for mission-critical data systems
Partner with Enterprise Data Platform team to implement automation and AI accelerator initiatives, and DevOps practices to enhance deployment speed and operational reliability
Manage technology budgets, vendor relationships, and strategic partnerships to optimize total cost of ownership
Leverage AI in Data Engineering lifecycle, accelerate code generation, and design and implement robust data pipelines (optimize SQL performance, and implement Self-Healing pipeline logic) supporting petabyte-scale data ingestion, transformation, and distribution
Ensure data platform security, compliance, and performance optimization across all environments