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

We are seeking a highly skilled Senior Data Specialist to join our dynamic team. In this role, you will provide technical leadership in designing, developing, and optimizing cloud-native data solutions on the Azure Data platform, with a primary focus on Azure Databricks. Your expertise will be instrumental in building enterprise-scale data pipelines, implementing modern 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 deep 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. You will play a pivotal role in designing and supporting robust Medallion Architecture patterns, while ensuring data quality, performance, security, and governance across the enterprise. Collaborating closely with architects, product teams, analytics stakeholders, and governance teams, you will deliver scalable, reusable, and production-ready data engineering solutions within a highly regulated setting.

Qualifications To succeed in this role, candidates should possess a strong technical background combined with 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 deep hands-on experience 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. Extensive experience with Azure Data Factory, Azure Data Lake Storage, Delta Lake, Delta Live Tables, CDC, and Medallion Architecture is required. Knowledge of data modeling, data warehousing, metadata management, and governance best practices is crucial.

Additionally, familiarity with CI/CD processes, automated testing, and troubleshooting complex data pipelines is necessary.

Preferred qualifications include experience with Snowflake, Kafka, streaming architectures, AI/ML workloads, and certifications in Azure and Databricks, which are highly desirable.

Responsibilities

- Design, build, and optimize large-scale data pipelines utilizing Azure Databricks, PySpark, and advanced SQL techniques.
- Develop and maintain batch and near real-time data ingestion frameworks using Azure Data Factory, Delta Lake, and CDC methodologies.
- Create and support modern Lakehouse solutions leveraging Medallion Architecture, including Bronze, Silver, and Gold layers.
- Implement Delta Live Tables pipelines to enhance data reliability, maintainability, and quality.
- Develop scalable and resilient ETL/ELT frameworks capable of processing high-volume enterprise datasets efficiently.
- Optimize Spark workloads, including job orchestration, partitioning strategies, and SQL performance tuning for large-scale environments.
- Establish and maintain data quality validation frameworks, lineage tracking,



metadata management, and governance controls.
- Implement automated testing and reconciliation processes to ensure data accuracy, completeness, and consistency.
- Collaborate with cross-functional teams to translate business requirements into technical solutions, ensuring alignment with enterprise standards.
- Drive engineering best practices, conduct code reviews, promote CI/CD adoption, and develop reusable frameworks.
- Mentor junior engineers, providing technical guidance and support on Databricks and Azure-based implementations.
- Evaluate emerging Azure and Databricks capabilities, recommending enhancements to improve platform performance and operational efficiency.

Benefits McKesson offers a comprehensive and competitive benefits package as part of our Total Rewards program. Our offerings include health insurance, retirement plans, paid time off, professional development opportunities, and wellness programs. The company values work-life balance and provides adaptable working arrangements to accommodate personal needs. We also support continuous learning through training and certification programs, fostering growth and career advancement within the organization. Compensation is aligned with industry standards and reflects experience, skills, and performance, with additional incentives such as annual bonuses or long-term incentives available based on individual and company performance.

Equal Opportunity

McKesson is an Equal Opportunity Employer that provides equal employment opportunities to all applicants and employees, regardless of 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 committed to fostering an inclusive environment where everyone can thrive. For additional information on our Equal Employment Opportunity policies, please visit our website.

We also offer reasonable accommodations to applicants with disabilities during the hiring process. If you require assistance,

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