Job Description

Salary: $99,100 - 132,100 per year Requirements:

• We require a bachelors degree, or an equivalent mix of education and professional experience; a masters degree is preferred.
• We typically look for 7+ years of relevant experience in data engineering, analytics, or a closely related discipline.
• We need strong expertise in building and supporting scalable data pipelines, ETL/ELT workflows, and enterprise data integration.
• We expect advanced proficiency in SQL and Python for data processing, performance tuning, and analytics support; R is a plus.
• We value solid knowledge of data modeling, data architecture, metadata management, and governance practices.
• We prefer hands-on experience with modern platforms and tools such as Databricks, Snowflake, Azure Data Factory, and PySpark.
• We look for familiarity with big data and distributed technologies such as Hadoop, Kafka, and distributed file systems.
• We want experience applying data standardization, reliability, quality improvement, and stewardship practices.
• We prefer candidates who have built custom components, analytics applications, and solutions enabling advanced analytics or AI use cases.
• We value familiarity with cloud environments and architectures, especially Azure, including SaaS, PaaS, and IaaS concepts.
• We seek effective communication and leadership skills to influence technical direction and mentor team members.
• Experience in healthcare or other regulated industries is strongly preferred.

• We design and deliver scalable data pipelines and ETL/ELT programs that connect complex internal and external data sources for batch and real-time processing.
• We write and refine advanced SQL and Python solutions to improve data handling, performance, and analytical results.
• We lead data discovery, requirements gathering, and source identification for analytical and operational initiatives.
• We build and maintain metadata repositories, including definitions, lineage, and business rules, to support data integrity and usability.
• We create and sustain processes that improve data standardization, reliability, quality, and governance compliance.
• We troubleshoot and resolve complex data and analytics issues across production and development environments, including tuning databases and pipelines.
• We develop reusable query libraries and custom software components that support analytics, reporting, and AI/ML solutions.
• We assess and implement modern tools, technologies, and best practices to strengthen our data engineering capabilities and platform performance.
• We ensure compliance with governance, security, and regulatory requirements through robust validation, quality checks, and documentation.
• We support testing, monitoring, and validation of data pipelines by creating test cases and verification checks.
• We collaborate with architects, analysts, data scientists, and governance partners to align solutions with enterprise standards and business priorities.
• We provide technical leadership, help shape design decisions, and mentor junior engineers to promote best practices and continuous improvement.

• AI
• Azure
• Big Data
• Cloud
• Databricks
• ETL
• Hadoop
• IaaS
• Support
• Kafka
• PaaS
• Python
• PySpark
• SQL
• Security
• Snowflake

More:

We are McKesson, an impact-driven Fortune 10 healthcare company focused on making care more accessible and affordable through our insights, products, and services. We foster a culture where people can grow, make an impact, and contribute new ideas as we help shape the future of health for patients, communities, and our teams. This Sr Data Specialist role sits within our enterprise data environment and supports advanced analytics and AI-driven use cases. We offer a competitive total rewards package, with a base pay range of $99,100 to $132,100, and our Flex and Connect model requires two in-office days per week. We are an equal opportunity employer and are committed to inclusive hiring and workplace practices.

last updated 39 week of 2026

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