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 plays a pivotal role in designing, developing, and optimizing cloud-native data solutions on the Azure Data platform, with a primary focus on Azure Databricks. This position involves building enterprise-scale data pipelines, implementing modern lakehouse architectures, and enabling 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 (ADF), Azure Data Lake Storage (ADLS), Delta Lake, Delta Live Tables (DLT), and Change Data Capture (CDC) frameworks. They will be responsible for supporting robust Medallion Architecture patterns while ensuring data quality, performance, security, and governance across the organization. Working closely with architects, product teams, analytics stakeholders, and governance teams, this role requires delivering scalable, reusable, and production-ready data engineering solutions in a highly regulated environment.

Qualifications The successful candidate will have a strong technical background combined with business acumen. 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 seven years of experience in data engineering and enterprise data platform development,



with a minimum of three years in hands-on Azure Databricks engineering in production environments.

Proven experience in building and supporting enterprise-scale data pipelines and Lakehouse architectures is essential.

Experience working with large volumes of structured and semi-structured data, preferably within healthcare, pharmaceuticals, life sciences, or other regulated industries, is highly desirable.

Technical skills required include expert-level proficiency in Azure Databricks, PySpark, SQL, Azure Data Factory, Azure Data Lake Storage, Delta Lake, Delta Live Tables, CDC, and Medallion Architecture. Knowledge of data modeling, data warehousing, metadata management, and governance best practices is necessary. Certifications in Azure and Databricks are highly preferred.

Responsibilities

Design, develop, and optimize large-scale data pipelines using Azure Databricks, PySpark, and advanced SQL techniques to support diverse analytics and AI/ML workloads. Implement and maintain batch and near real-time data ingestion frameworks leveraging Azure Data Factory, Delta Lake, and CDC methodologies. Build and support modern Lakehouse solutions utilizing Medallion Architecture, ensuring data is processed efficiently and securely across bronze, silver, and gold layers.

Create and support Delta Live Tables pipelines that enhance data reliability, maintainability, and quality. Develop scalable and resilient ETL/ELT frameworks capable of processing high-volume enterprise datasets. Optimize Spark workloads through partitioning strategies, job orchestration, and performance tuning to ensure productive operation at scale. Implement monitoring, alerting, troubleshooting, and performance-tuning practices to maintain high levels of pipeline health and data quality.

Establish and uphold data quality validation frameworks, lineage tracking,



metadata management, and governance controls. Automate testing, reconciliation, and validation processes to ensure data accuracy, completeness, and consistency. Support regulatory, security, and compliance requirements through well-documented controls and audit-ready processes.

Collaborate with architects and stakeholders to translate business requirements into scalable technical solutions. Drive engineering best practices, conduct code reviews, and promote CI/CD adoption. Mentor junior engineers and provide technical leadership on Databricks and Azure-based implementations. Continuously evaluate emerging Azure and Databricks features, recommending enhancements to improve platform performance and operational efficiency.

Benefits

McKesson offers a comprehensive benefits package as part of our Total Rewards program. This includes competitive compensation aligned with experience and performance, health insurance, retirement plans, paid time off, and wellness programs. We also provide opportunities for professional development, continuous learning, and career advancement.

Our flexible work arrangements, including a hybrid model requiring two days in the office per week, support work-life balance. Additional benefits may include performance bonuses, long-term incentives, and employee assistance programs, all designed to support your well-being and growth within the company.

Equal Opportunity

McKesson is an Equal Opportunity Employer. We are committed to providing a work environment free from discrimination and harassment. 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 value diversity and inclusion and strive to create a workplace where all individuals can thrive. If you require a reasonable accommodation during the application process, please contact us via the designated channels. For more information about our Equal Employment Opportunity policies, please visit our official page.

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