About The Company

- Senior Data Specialist at McKesson

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 primarily on the Azure Data platform, with a focus on Azure Databricks. This role 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 decisions. The ideal candidate will bring extensive hands-on experience with Databricks, PySpark, advanced SQL, and various Azure data services, ensuring the delivery of scalable, reliable, and secure data solutions in a highly regulated environment.

This position requires close collaboration with architects, product teams, analytics stakeholders, and governance teams to ensure data quality, security, and compliance.

The Senior Data

Specialist will be responsible for supporting and enhancing data engineering frameworks, mentoring junior engineers, and driving best practices across the organization to support McKesson's mission of improving healthcare outcomes through innovative data solutions.

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

Key technical skills include expert-level proficiency in Azure Databricks, PySpark, and advanced SQL, along with extensive experience with Azure Data Factory, Azure Data Lake Storage Gen2, Delta Lake, Delta Live Tables, Change Data Capture frameworks, and Medallion Architecture. Knowledge of data modeling, data warehousing, metadata management, and data governance is essential.

Experience with CI/CD processes, automated testing, and troubleshooting complex data pipelines is also required.

Preferred skills include familiarity with Snowflake, Kafka, streaming architectures, and AI/ML workloads within Databricks, along with relevant certifications.

Responsibilities

- Design, build, and optimize large-scale data pipelines utilizing Azure Databricks, PySpark, and advanced SQL techniques to support enterprise analytics and AI initiatives.
- Develop and maintain batch and near real-time data ingestion frameworks using Azure Data Factory, Delta Lake, and CDC methodologies to ensure timely and accurate data flow.
- Implement and support modern Lakehouse architectures leveraging Medallion Architecture (Bronze, Silver, Gold layers) for scalable data management.
- Create and manage Delta Live Tables pipelines to enhance data reliability, maintainability, and quality control.
- Build resilient ETL/ELT frameworks capable of processing high volumes of structured and semi-structured data efficiently.
- Optimize Spark workloads, including partitioning strategies, job orchestration,



and SQL performance tuning to maximize processing efficiency.
- Establish monitoring, alerting, and troubleshooting practices to maintain high pipeline availability and performance.
- Implement data quality validation frameworks, lineage tracking, metadata management, and governance controls to ensure compliance and data integrity.
- Collaborate with cross-functional teams to translate business requirements into scalable technical solutions, providing technical leadership and mentorship to junior staff.
- Evaluate emerging Azure and Databricks capabilities, recommending platform enhancements to improve performance and operational efficiency.

Benefits McKesson offers a comprehensive and competitive total rewards package, including base salary, annual bonuses, and long-term incentives. Our benefits program encompasses health, dental, vision insurance, retirement plans, paid time off, and wellness initiatives designed to support your overall well-being. We also provide opportunities for professional development, continuous learning, and career advancement. Our flexible work arrangements, including a hybrid mode requiring two days in the office per week, support work-life balance. At McKesson, we are committed to fostering an inclusive environment that values diversity and promotes growth for all employees.

Equal Opportunity

McKesson is an Equal Opportunity Employer. We provide equal employment opportunities to applicants and employees without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, age, genetic information, or any other legally protected category. We are dedicated to creating an inclusive workplace where everyone feels valued and respected.

If you require a reasonable accommodation during the application process, please contact us via email. McKesson does not solicit or accept money or credit card information in connection with job applications, and all official communications originate from our verified channels.

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