Data Specialist

MCKESSON; Little Canada (MN); Hybrid; USD 82,000 - 109,000; Full time

Benefits offered by this job

Hybrid work (two days in office)

Job summary

McKesson is seeking a hands-on Data Specialist to design and maintain enterprise healthcare data pipelines using Databricks, Delta Lake, and Apache Spark. You will build scalable ETL/ELT processes for enterprise reporting and analytics, and collaborate with engineering, analytics, and product teams to meet business needs.

The role requires strong SQL and Python skills, experience with BI tools (Power BI/Tableau), and familiarity with GitHub-based CI/CD in Agile environments.

Qualifications

• Bachelor's degree in computer science, software engineering, information systems, data science, or related discipline; or equivalent experience.
• 4+ years in data engineering, database engineering, software engineering, or related technical field.
• 3+ years of hands-on SQL and relational database experience.
• 2+ years of Python development and automation experience.
• 2+ years using Databricks, Spark, or modern cloud data platforms.
• Experience with Power BI and/or Tableau.
• Experience in Agile development environments and using GitHub & CI/CD processes.
• Strong analytical, troubleshooting, and problem-solving skills.
• Hands-on expertise with Databricks, Delta Lake, Apache Spark; advanced SQL; strong Python for automation, data processing, integration, analytics.
• Experience designing and maintaining enterprise-scale data pipelines and processing frameworks.
• Experience with workflow orchestration tools (Databricks Workflows, Airflow, or equivalent).
• Understanding of modern data warehousing/lakehouse architectures and analytics best practices.
• Knowledge of GitHub source control practices (branch protections, PR reviews, release management).
• Experience building CI/CD pipelines (GitHub Actions) and testing, deployment automation, and infrastructure best practices.
• Experience using AI development tools (Claude Code, GitHub Copilot or equivalent).
• Preferred: Azure experience, healthcare analytics platforms, HL7/FHIR, data quality observability, ML, AI-enabled healthcare solutions.

Responsibilities

• Design, develop, and maintain scalable data pipelines using Databricks, Delta Lake, Spark, SQL and Python.
• Build and optimize ETL/ELT processes for enterprise reporting, analytics, and operational data needs.
• Create efficient data models and database solutions for high-performance analytics and BI.
• Collaborate with engineers, product, analytics, and operations to translate business needs into scalable data solutions.
• Maintain data quality, governance, and security across healthcare data platforms.
• Support data ingestion, transformation, and integration for business use cases.
• Establish data validation, monitoring, and observability for reliable operations.
• Design and support workflow orchestration using Databricks Workflows, Airflow, or similar tools.
• Contribute to cloud data modernization and enterprise analytics platform initiatives.
• Develop and maintain CI/CD pipelines using GitHub and modern DevOps practices; use AI-assisted development tools.

Job description

Salary: $81,500 - 108,600 per year

Requirements: Bachelors degree in computer science, software engineering, information systems, data science, or a related discipline, or equivalent experienceAt least 4 years of relevant professional experience4+ years in data engineering, database engineering, software engineering, or a related technical field3+ years of hands-on SQL and relational database experience2+ years of Python development and automation experience2+ years using Databricks, Spark, or modern cloud data engineering platformsExperience with Power BI and/or TableauExperience working in Agile development environments and using GitHub and
CI/CD
processesStrong analytical, troubleshooting, and problem-solving skillsHands-on expertise with Databricks, Delta Lake, and Apache Spark; advanced SQL skills for complex queries, performance tuning, data modeling, and optimization; and strong Python programming skills for automation, data processing, integration, and analyticsExperience designing and maintaining enterprise-scale data pipelines and processing frameworksExperience with workflow orchestration tools such as Databricks Workflows, Apache Airflow, or equivalent technologiesUnderstanding of modern data warehousing, lakehouse architectures, and analytics best practicesKnowledge of GitHub source control practices, including branch protections, pull request reviews, release management, and version controlExperience building and maintaining CI/CD pipelines, including with GitHub Actions, and familiarity with automated testing, deployment automation, and infrastructure best practicesExperience using AI development tools such as Claude Code, GitHub Copilot, or equivalentPreferred: Experience with Azure, large-scale healthcare analytics platforms, HL7 or FHIR, data quality frameworks, data observability, enterprise reporting modernization, or machine learning, predictive analytics, and AI-enabled healthcare solutions

Responsibilities: Design, develop, and maintain scalable data pipelines using Databricks, Delta Lake, Apache Spark, SQL, and PythonBuild and optimize ETL/ELT processes for enterprise reporting, analytics, and operational data needsCreate efficient data models and database solutions for high-performance analytics and business intelligenceWork with Forward Deployed Engineers and business, product, and analytics stakeholders to turn business needs into scalable data solutionsMaintain data quality, integrity, governance, and security across healthcare data platformsSupport the ingestion, transformation, and integration of datasets for business use casesEstablish data validation, monitoring, and observability practices to support reliable operationsDesign and support workflow orchestration using Databricks Workflows, Apache Airflow, or similar toolsContribute to cloud data modernization and enterprise analytics platform initiativesDevelop and maintain CI/CD pipelines and deployment processes using GitHub and modern DevOps practicesUse AI-assisted development tools to improve engineering productivity, code quality, testing, documentation, and delivery efficiencyParticipate in Agile activities, including sprint planning, backlog refinement, estimation, and retrospectivesDiagnose complex data and performance issues and implement sustainable solutionsCollaborate with teams across engineering, architecture, product management, analytics, and operations

Technologies: AIAirflowAzureBusiness IntelligenceCI/CDClaude CodeCloudCopilotDatabricksDevOpsETLGitHubHL7SupportMachine LearningPower BIPythonSQLSecuritySparkTableauMore:

We are McKesson, an impact-driven Fortune 10 company working across healthcare to make quality care more accessible and affordable. At McKesson, we support growth, new ideas, and meaningful contributions as we work to shape the future of health for patients, communities, and our people. Our Provider Solutions team is seeking a hands-on Data Specialist to help build and improve enterprise healthcare data platforms, analytics, and cloud data engineering capabilities. The role works closely with engineering, analytics, product, and business teams and supports healthcare data governance and regulatory compliance. This is a Flex and Connect position requiring two days per week in the office. We offer a competitive total rewards package, with base pay of $81,500–$108,600 and potential annual bonus or long-term incentives. We are an equal opportunity employer.last updated 41 week of 2026