Sr. Data Specialist

Responsibilities

• Design and deploy cloud-native data applications and pipelines using Azure and Databricks to enable advanced analytics and digital capabilities across pharmaceutical business domains.
• Manage offshore and nearshore teams to deliver validated, governed, and scalable data products. Promote robust metadata management, data lineage, and domain-driven design.
• Collaborate with data and platform architecture teams to align data product designs with enterprise architecture standards and governance frameworks.
• Define and enforce best practices for data quality, scalability, and performance. Provide technical leadership and mentorship to global engineering teams.
• Establish standardized dimensional models (Facts, Dims), ontologies, and semantic structures to ensure interoperability and consistency across data domains.
• Apply AI-enabled SDLC practices and automation to enhance performance, reduce technical debt, and accelerate time-to-market for data products.
• Drive seamless data integration across platforms, champion modernization through Azure-native technologies, and optimize workflows for performance, reliability, and cost-efficiency.
• Required Qualifications
• Bachelor's degree in computer science, Engineering, or a related field.
• 7+ years of strong data engineering experience in building data solutions and data products.
• 3+ years of proven Data architecture background in enabling the creation of enterprise data solutions.
• Expert hands-on experience with Azure, Databricks, and Snowflake data warehousing.

Requirements

• Preferably 2+ years of experience in supply chain analytics - specifically Transportation, Inventory management and CRM analytics.
• Relevant certifications in Azure, Databricks, Snowflake, data modeling and other cloud native data management tools/platforms add significantly to your case.
• Working Conditions
• In office requirements, we are Flex and Connect with 2 days a week in office
• Our Base Pay Range for this position
• $99,100 - $132,100
• McKesson Talent Advisors will never solicit money or credit card information in connection with a McKesson job application.
• McKesson Talent Advisors do not communicate with candidates via online chatrooms or using email accounts such as Gmail or Hotmail. Note that McKesson does rely on a virtual assistant (Gia) for certain recruiting-related communications with candidates.
• McKesson job postings are posted on our career site: careers.mckesson.com .
• McKesson is an Equal Opportunity Employer
• McKesson provides equal employment opportunities to applicants and employees, without regard to

Benefits

Additional Information

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 experienced Sr Data Engineer to join McKesson Technology Pharmaceutical Solutions and Services (PSaS) DI Data Architecture and Engineering organization. This individual will provide in-depth advanced data product architecture and engineering and analytical insight, while working in a collaborative environment to solve business problems. This person will work cross-functionally with other technology teams, data scientists/analysts, BI Developers, data architects, data engineers, and delivery leaders to design and develop data solutions, data products, insights, and analytic models to help key stakeholders make better informed decisions. This role bolsters our supply chain organization modernization strategic efforts by enabling rapid AI/ML experimentation and operationalization of proven use cases and monetization of insights.

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