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 vital role responsible for leading the design, development, and optimization of cloud-native data solutions on the Azure Data platform, with a particular emphasis on Azure Databricks. This position 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 (ADF), Azure Data Lake Storage (ADLS), Delta Lake, Delta Live Tables (DLT), and Change Data Capture (CDC) frameworks. This individual will play a crucial role in designing and supporting robust Medallion Architecture patterns while ensuring data quality, performance, security, and governance across the organization.

This role requires close collaboration with architects, product teams, analytics stakeholders, and governance teams to deliver scalable, reusable, and production-ready data engineering solutions within a highly regulated environment.

The Senior Data

Specialist will also mentor junior engineers and provide technical leadership to ensure best practices are followed in all data engineering initiatives.

Qualifications To succeed in this role, candidates should possess a combination of technical expertise, industry experience, and a strong educational background.



A Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field 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, including a minimum of 3+ years of hands-on experience with Azure Databricks in production environments.

Proven experience in building and supporting large-scale data pipelines and Lakehouse implementations is essential. Candidates must demonstrate deep knowledge of data modeling, data warehousing, metadata management, and governance best practices. Familiarity with cloud-native architecture, CI/CD pipelines, automated testing, and production deployment processes is also required.

Strong problem-solving skills, troubleshooting abilities, and a proactive approach to performance tuning and optimization are vital.

Certifications in Azure and Databricks are highly preferred, along with experience working in regulated industries such as healthcare, pharmaceuticals, or life sciences.

Responsibilities

Azure Databricks & Data Engineering

- Design, build, and optimize large-scale data pipelines using Azure Databricks, PySpark, and advanced SQL techniques.
- Develop and maintain batch and near real-time data ingestion frameworks utilizing Azure Data Factory, Delta Lake, and CDC methodologies.
- Create and support modern Lakehouse solutions following Medallion Architecture (Bronze, Silver, Gold layers) for scalable data management.
- Implement Delta Live Tables (DLT) pipelines to enhance data reliability, maintainability, and quality.
- Build highly scalable and resilient ETL/ELT frameworks capable of processing high-volume enterprise datasets efficiently.




- Optimize Spark workloads, partitioning strategies, and job orchestration to improve performance and resource utilization.
- Establish monitoring, alerting, troubleshooting, and performance tuning practices to ensure smooth data pipeline operations.

Data Quality & Governance

- Implement data quality validation frameworks, lineage tracking, metadata management, and governance controls to ensure data integrity.
- Automate testing and reconciliation processes to maintain data accuracy, completeness, and consistency across systems.
- Support compliance, security, and regulatory requirements through documented controls and audit-ready processes.

Solution Delivery & Leadership

- Collaborate with architecture and business teams to translate requirements into scalable technical solutions.
- Drive engineering best practices, code reviews, CI/CD adoption, and reusable framework development to enhance team efficiency.
- Mentor junior engineers, fostering knowledge sharing and technical growth within the team.
- Evaluate emerging Azure and Databricks capabilities, 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 programs. We also provide opportunities for professional development, continuous learning, and career advancement. As part of our commitment to work-life balance, we offer flexible work arrangements and a supportive work environment. Extra benefits may include performance bonuses, long-term incentives, and employee assistance programs.

Equal Opportunity

McKesson is an Equal Prospect Employer that values diversity and inclusion in the workplace. We provide equal employment opportunities to all applicants and employees without regard to race, color, religion, sex, sexual orientation, gender

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