Senior Data Specialist

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.

Summary The Senior Data Specialist provides technical leadership in designing, developing, and optimizing cloud-native data solutions on the Azure Data platform, with a primary focus on Azure Databricks. This role is responsible for building enterprise-scale data pipelines, implementing modern lakehouse architectures, and enabling trusted, high-quality data products that support analytics, AI/ML, and business decision-making. The ideal candidate brings 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. This individual will play a key role in designing and supporting robust Medallion Architecture patterns while ensuring data quality, performance, security, and governance across the enterprise. Working closely with architects, product teams, analytics stakeholders, and governance teams, the Senior Data Specialist will deliver scalable, reusable, and production-ready data engineering solutions in a highly regulated environment.

Azure Databricks & Data Engineering Design, build, and optimize large-scale data pipelines using Azure Databricks, PySpark, and advanced SQL. Develop and maintain batch and near real-time data ingestion frameworks using Azure Data Factory (ADF), Delta Lake, and CDC methodologies. Build and support modern Lakehouse solutions leveraging Medallion Architecture (Bronze, Silver, Gold layers). Design and implement Delta Live Tables (DLT) pipelines to improve reliability, maintainability, and data quality. Develop highly scalable and resilient ETL/ELT frameworks that process high-volume enterprise datasets. Optimize Spark workloads, partitioning strategies, job orchestration, and SQL performance for large-scale processing environments. Implement robust monitoring, alerting, troubleshooting, and performance-tuning practices across data pipelines. Data Quality & Governance 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. Support regulatory, security, and compliance requirements through documented controls and audit-ready processes. Solution Delivery & Leadership Collaborate with architects and stakeholders to translate business requirements into scalable technical solutions. Drive engineering best practices, code reviews, CI/CD adoption, and reusable framework development. Mentor junior engineers and provide technical leadership on Databricks and Azure-based implementations. Evaluate emerging Azure and Databricks capabilities and recommend enhancements to improve platform performance and operational efficiency.

(Knowledge, Skills & Abilities) Required Technical Skills Expert-level hands-on Azure Databricks experience designing, building, and supporting enterprise-grade data solutions. Strong expertise in PySpark and advanced SQL for large-scale data processing and optimization. Extensive experience with: Azure Data Factory (ADF) Azure Data Lake Storage (ADLS Gen2) Delta Lake Delta Live Tables (DLT) Change Data Capture (CDC) Medallion Architecture Deep understanding of Spark architecture, job optimization, partitioning