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 key technical leader responsible for designing, developing, and optimizing 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 modern lakehouse architectures, and enabling high-quality, trusted data products that support analytics, artificial intelligence, machine learning, and strategic business decisions.

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 crucial role in designing and supporting robust Medallion Architecture patterns while ensuring data quality, performance, security, and governance across the organization. Collaborating closely with architects, product teams, analytics stakeholders, and governance units, the Senior Data Specialist will deliver scalable, reusable, and production-ready data engineering solutions within a highly regulated environment.

Qualifications The successful candidate will have a strong technical background complemented by relevant industry experience. A bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field 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 direct, hands-on experience working with Azure Databricks in production environments.

Proficiency in designing, building, and supporting enterprise-grade data solutions using Azure Databricks, PySpark, and advanced SQL is essential. Knowledge of data modeling, data warehousing, metadata management, and governance best practices is critical.

Experience with Azure Data Factory, Azure Data Lake Storage, Delta Lake, Delta Live Tables, CDC, and Medallion Architecture is required. Familiarity with CI/CD pipelines, automated testing, and troubleshooting complex data pipeline issues is also necessary.

Preferred qualifications include experience with Snowflake, Kafka, streaming architectures, AI/ML workloads, and relevant Azure or Databricks certifications.

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 real-time data ingestion frameworks utilizing Azure Data Factory, Delta Lake, and CDC methodologies to ensure timely data availability.
- Create and support modern Lakehouse solutions based on Medallion Architecture, comprising Bronze, Silver, and Gold data layers, to facilitate scalable and high-quality data management.
- Implement Delta Live Tables (DLT) pipelines to enhance reliability, maintainability, and data quality across data workflows.
- Develop scalable ETL/ELT frameworks capable of processing high-volume enterprise datasets efficiently and securely.
- Optimize Spark workloads through effective partitioning, job orchestration, and performance tuning strategies to maximize processing efficiency.
- Establish monitoring, alerting, troubleshooting,



and performance tuning practices to maintain optimal data pipeline operations.
- Implement data quality validation, lineage tracking, metadata management, and governance controls to ensure compliance and data integrity.
- Collaborate with cross-functional teams to translate complex business requirements into scalable technical solutions.
- Drive best practices in data engineering, code reviews, CI/CD implementation, and reusable framework development.
- Mentor junior engineers, fostering a culture of continuous learning and technical excellence.
- Evaluate emerging Azure and Databricks features, recommending enhancements to improve platform performance and operational efficiency.

Benefits McKesson offers a comprehensive benefits package designed to support the health, well-being, and financial security of our employees. Our Total Rewards program includes competitive compensation, health insurance options, retirement plans, paid time off, and wellness initiatives. We also provide opportunities for professional development, continuous learning, and career advancement. Our flexible work arrangements, including a hybrid model requiring two days per week in the office, support work-life balance. Additional perks may include performance bonuses, long-term incentives, and employee assistance programs, all aimed at fostering a supportive and engaging work workplace.

Equal Opportunity

McKesson is an Equal Opportunity Employer committed to creating an inclusive environment for all employees and applicants. 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 promote diversity and inclusion in our workforce and are dedicated to providing reasonable accommodations to qualified individuals with disabilities during the application process.

For more information on our Equal Employment Opportunity policies, please visit our website. We welcome all qualified candidates to join us in shaping the future of healthcare.

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