About The Company 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.

About The Role The Senior Data Specialist at McKesson is a pivotal role responsible for leading the design, development, and optimization of cloud-native data solutions on the Azure Data platform, with a primary focus on Azure Databricks. This role involves building enterprise-scale data pipelines, implementing up-to-date lakehouse architectures, and enabling the creation of trusted, high-quality data products that support analytics, artificial intelligence, machine learning, and strategic business decision-making.

The ideal candidate will possess extensive hands-on experience with Databricks, PySpark, advanced SQL, Azure Data Factory, Azure Data Lake Storage, Delta Lake, Delta Live Tables, and Change Data Capture frameworks. They will play a critical role in designing and supporting robust Medallion Architecture patterns, ensuring data quality, performance, security, and governance across the enterprise. Working closely with architects, product teams, analytics stakeholders, and governance teams, this individual will deliver scalable, reusable, and production-ready data engineering solutions within a highly regulated environment.

Qualifications To succeed in this role, candidates should possess a combination of technical expertise, industry experience, and leadership skills. A bachelor's degree in Computer Science, Engineering, Information Systems, or a related discipline is required; a master's degree is preferred.

Candidates should have at least 7+ years of experience in data engineering and enterprise data platform development,



with a minimum of 3+ years of deep, hands-on experience with Azure Databricks in production environments.

Strong proficiency in PySpark and advanced SQL is essential for large-scale data processing and optimization. Extensive experience with Azure Data Factory, Data Lake Storage, Delta Lake, Delta Live Tables, Change Data Capture, and Medallion Architecture is required. Knowledge of Spark architecture, job optimization, partitioning strategies, and performance tuning is critical.

Additionally, familiarity with data modeling, data warehousing, metadata management, and governance practices is necessary to ensure compliance and data integrity.

Preferred qualifications include experience with Snowflake, Kafka, streaming architectures, event-driven processing, and AI/ML workloads within Databricks. Certifications in Azure and Databricks are highly desirable.

Responsibilities

- Design, build, and optimize large-scale data pipelines leveraging Azure Databricks, PySpark, and advanced SQL techniques to support enterprise data needs.
- Develop and maintain batch and near real-time data ingestion frameworks using Azure Data Factory, Delta Lake, and CDC methodologies to ensure data freshness and reliability.
- Create and support modern Lakehouse architectures based on Medallion Architecture (Bronze, Silver, Gold layers) to enable scalable and efficient data processing.
- Design and implement Delta Live Tables pipelines to enhance data reliability, maintainability, and quality across various data domains.
- Develop resilient ETL/ELT frameworks capable of processing high-volume datasets, ensuring performance and scalability.
- Optimize Spark workloads through effective partitioning, job orchestration, and SQL performance tuning to improve processing efficiency.




- Implement monitoring, alerting, troubleshooting, and performance tuning practices for data pipelines to ensure high availability and operational excellence.
- Establish and maintain data quality validation frameworks, lineage tracking, metadata management, and governance controls to support compliance and audit readiness.
- Collaborate with cross-functional teams to translate business requirements into scalable technical solutions, ensuring alignment with enterprise standards.
- Drive engineering best practices, conduct code reviews, promote CI/CD adoption, and develop reusable frameworks for data engineering projects.
- Mentor junior engineers, providing technical guidance and fostering a culture of continuous learning and improvement.
- Evaluate emerging Azure and Databricks capabilities, recommending enhancements to platform performance, security, and operational efficiency.

Benefits McKesson offers a comprehensive benefits package as part of our Total Rewards program. This includes competitive compensation, health insurance, retirement plans, paid time off, and opportunities for professional growth. We also provide flexible work arrangements, wellness programs, and ongoing learning opportunities to support your personal and professional development. Our commitment to employee well-being and work-life balance is central to our culture. Salary for this position ranges from $99,100 to $132,100, determined by experience, skills, and performance. In addition to base pay, eligible employees may receive bonuses, long-term incentives, and other benefits aligned with company policies and market standards.

Equal Opportunity

McKesson is an Equal Opportunity Employer. We are committed to creating a diverse and inclusive environment where all individuals are treated with respect and fairness. We do not discriminate based on race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, age, genetic information, or any other legally protected category. We encourage applicants from all backgrounds to apply.

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