Job Description

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

• We need a bachelors degree or an equivalent mix of education and experience; a masters degree is preferred.
• We typically look for 7+ years of relevant experience in data engineering, analytics, or a closely related field.
• We expect advanced hands-on experience with ETL/ELT development, SQL and Python scripting, and enterprise data integration across multiple platforms.
• We prefer exposure to modern data ecosystems and large-scale data processing frameworks.
• Experience in healthcare or another regulated industry is strongly preferred.
• We value expertise in scalable data pipeline design, data modeling, data architecture, metadata management, and governance practices.
• We look for proficiency with tools such as Databricks, Snowflake, Azure Data Factory, and PySpark.
• Familiarity with Hadoop, Kafka, distributed file systems, and cloud environments, especially Azure, is preferred.
• Strong communication and leadership skills are important for influencing stakeholders and mentoring team members.

• We design and implement scalable data pipelines and ETL/ELT solutions that integrate complex internal and external data sources for batch and real-time processing.
• We write and tune advanced SQL and Python queries to improve data processing, performance, and analytical results.
• We lead data discovery, requirements analysis, and source identification for analytical and operational initiatives.
• We build and maintain metadata repositories, including data definitions, lineage, and business rules, to support data trust and usability across the enterprise.
• We create and improve processes for data standardization, reliability, quality enhancement, and governance compliance.
• We troubleshoot and resolve complex data and pipeline issues across development and production, including performance tuning for databases and workflows.
• We develop reusable query libraries and custom software components to support analytics, reporting, and AI/ML solutions.
• We recommend and adopt modern tools, technologies, and best practices to strengthen our data engineering capabilities and platform performance.
• We ensure governance, security, and regulatory requirements are met through thorough quality checks, validation, and documentation.
• We support testing, monitoring, and validation of data pipelines, including test case creation and quality controls.
• We collaborate with architects, analysts, data scientists, and governance teams to align solutions with enterprise architecture and business priorities.
• We provide technical guidance, shape design decisions, and mentor junior engineers to promote best practices and continuous improvement.

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

More:

We are McKesson, an impact-driven Fortune 10 healthcare company focused on making quality care more accessible and affordable. This Senior Data Specialist role supports our enterprise data infrastructure and advanced analytics efforts, with an automation-first and enterprise-first mindset. We offer a competitive total rewards package, potential bonus and long-term incentive opportunities, and a Flex and Connect work model with two days per week in the office. We are committed to equal employment opportunity and a culture where our people can grow, make an impact, and help shape the future of health.

last updated 39 week of 2026

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