McKesson
Healthcare
DirectorofDataEngineering
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“Director of Data Engineering at McKesson. Skills: Data Engineering, Microsoft Azure, Databricks, AI-First Data Platforms. Set technical vision. Manage high-performing teams”
What You'll Achieve.
Deliver high-impact data solutions; Power critical business decisions; Maintain competitive advantage; Enhance deployment speed; Enhance operational reliability; Optimize total cost of ownership; Accelerate code generation; Support petabyte-scale data ingestion
Industry & Context.
Find solutions to complex technical issues
What They're Looking For.
Must Have
12+ years experience of professional experience in related IT field, 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, foundation in modern data architectures, scalable Lakehouse using Medallion patterns and Unity "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, technical aptitude and experience with a wide variety of technologies, Ability to rapidly learn and if required evaluate a new tool or technology, verbal & written communication skills, Demonstrated technical leadership experience, Be an innovative thinker, Must have a 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 Have
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)
What You'll Do.
Manage high-performing teams
Manage large-scale data products
Collaborate with stakeholders
Oversee data governance
Oversee data security
Oversee best practices
Define data architecture vision
Establish data engineering standards
Establish best practices
Establish governance frameworks
Design scalable data products
Build scalable data products
Maintain scalable data products
Lead Databricks implementation
Build high-performing team
Mentor high-performing team
Lead high-performing team
Collaborate cross-functionally
Deliver integrated solutions
Establish talent development programs
Establish technical career paths
Establish engineering excellence initiatives
Foster culture of innovation
Foster culture of continuous learning
Foster culture of technical excellence
Lead delivery of data products
Implement monitoring capabilities
Implement alerting capabilities
Implement incident response capabilities
Implement automation initiatives
Implement AI accelerator initiatives
Implement DevOps practices
Manage technology budgets
Manage vendor relationships
Manage strategic partnerships
Leverage AI in Data Engineering
Accelerate code generation
Design data pipelines
Implement data pipelines
Optimize SQL performance
Implement Self-Healing pipeline logic
Ensure data platform security
Ensure data platform compliance
Ensure data platform performance optimization
How You'll Work.
Team & Collaboration
Collaborate with executives; Collaborate with business leaders; Collaborate with technology stakeholders; Collaborate cross-functionally with Operations; Collaborate cross-functionally with Data Science; Collaborate cross-functionally with Analytics; Collaborate cross-functionally with IT; Collaborate cross-functionally with Business Intelligence teams; Work across organizational boundaries
Communication Scope
verbal & written communication skills
Full Job Description
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. We are 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. **Key Accountabilities:** * **Strategic Leadership** * 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 * **Technical Excellence** * Design, build, and maintain scalable and AI-ready data products leveraging Microsoft Azure ecosystem, ensuring efficient data
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