Senior Data Speaclist

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 decisions. The role requires a combination of technical expertise, innovative thinking, and collaborative engagement with cross-functional teams to deliver scalable and robust data solutions.

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 designing and supporting Medallion Architecture patterns, ensuring data quality, performance, security, and governance across the enterprise. Working closely with architects, product teams, analytics stakeholders, and governance units, the Senior Data Specialist will deliver production-ready data engineering solutions in a highly regulated environment, contributing to McKesson’s mission of transforming healthcare through data excellence.

Qualifications

To succeed in this role, candidates should possess a combination of technical skills, industry experience, and educational background:

• Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field; a Master’s degree is preferred.
• Minimum of 7 years of experience in data engineering and enterprise data platform development.
• At least 3 years of hands-on experience with Azure Databricks in a production environment.
• Deep expertise in PySpark and advanced SQL for large-scale data processing and optimization.
• Strong knowledge of Azure Data Factory, Azure Data Lake Storage Gen2, Delta Lake, Delta Live Tables, CDC, and Medallion Architecture.
• Proficiency in designing, building, and supporting end-to-end ETL/ELT pipelines in cloud-native environments.
• Understanding of data modeling, data warehousing, metadata management, and data governance best practices.
• Experience with CI/CD pipelines, automated testing, source control, and deployment processes.
• Exceptional troubleshooting skills for complex pipeline failures, data quality issues, and performance bottlenecks.

Preferred qualifications include experience with Snowflake, Kafka, streaming architectures, AI/ML workloads, and relevant Azure or Databricks certifications. Healthcare or regulated industry experience is highly advantageous.

Responsibilities

• Design, develop, and optimize large-scale data pipelines utilizing Azure Databricks, PySpark, and advanced SQL techniques to process high-volume datasets efficiently.
• Create and maintain batch and near real-time data ingestion frameworks using Azure Data Factory, Delta Lake, and CDC methodologies to ensure data freshness and accuracy.
• Implement and support modern Lakehouse architectures, leveraging the Medallion Architecture (Bronze, Silver, Gold layers) to organize and govern data effectively.
• Develop Delta Live Tables pipelines to enhance data reliability, maintainability, and quality, ensuring compliance with enterprise standards.
• Build scalable ETL/ELT frameworks capable of processing structured and semi-structured data, supporting analytics and AI/ML initiatives.
• Optimize Spark workloads through effective partitioning, job orchestration, and SQL performance tuning to maximize efficiency.
• Establish and maintain data quality validation frameworks, lineage tracking, metadata management, and governance controls to ensure data integrity and compliance.
• Collaborate with cross-functional teams, including architects, product managers, and compliance teams, to translate business requirements into technical solutions.
• Lead code reviews, promote engineering best practices, and support CI/CD adoption to ensure high-quality, maintainable codebases.
• Mentor junior engineers, fostering a culture of continuous learning and technical excellence.
• Evaluate emerging technologies and platform capabilities, recommending enhancements to improve performance, scalability, and operational efficiency.

Benefits

McKesson offers a comprehensive and competitive benefits package designed to support the health, well-being, and financial security of our employees. Our benefits include medical, dental, and vision insurance, life and disability coverage, and wellness programs. We also provide retirement plans, paid time off, and flexible work arrangements to promote work-life balance. Additionally, employees have access to professional development opportunities, tuition reimbursement, and employee assistance programs. We are committed to creating an inclusive environment that fosters growth, innovation, and success for all team members.

Equal Opportunity

McKesson is an Equal Opportunity Employer committed to diversity and inclusion. We provide equal employment opportunities to all applicants and employees without regard to race, color, religion, sex