Note: The job is a remote job and is open to candidates in USA. McKesson is an impact-driven healthcare company delivering products, services, and insights to improve access to quality care. The Data Engineer will design, develop, and optimize enterprise-scale healthcare data platforms, pipelines, analytics solutions, and cloud-based data engineering capabilities. The role collaborates with engineering, analytics, product, and business stakeholders while ensuring data quality, governance, security, and regulatory compliance.
Responsibilities
- Design, develop, and maintain scalable data pipelines using Databricks, Delta Lake, Apache Spark, SQL, and Python
- Build and optimize ETL/ELT processes to support enterprise reporting, analytics, and operational data needs
- Develop efficient data models and database solutions to enable high-performance analytics and business intelligence workloads
- Partner with business stakeholders, product teams, and analytics teams to translate business requirements into scalable data solutions
- Create and maintain dashboards, reports, and visualizations using Power BI and Tableau to provide actionable business insights
- Ensure data quality, integrity, governance, and security across healthcare data platforms
- Support ingestion, transformation, and integration of clinical, claims, provider, and patient datasets
- Implement data validation, monitoring, and observability processes to ensure data reliability and operational excellence
- Design and support workflow orchestration solutions using Databricks Workflows, Apache Airflow, or similar tools
- Contribute to cloud-based data modernization initiatives and enterprise analytics platforms
- Develop and maintain CI/CD pipelines and deployment processes utilizing GitHub and modern DevOps practices
- Apply AI-assisted development tools to improve engineering productivity, code quality, testing, documentation, and overall delivery efficiency
- Participate in Agile ceremonies including sprint planning, backlog refinement, estimation, and retrospectives
- Troubleshoot complex data and performance issues and implement sustainable solutions
- Collaborate effectively with cross-functional teams across engineering, architecture, product management, analytics, and operations
Skills
- *Applicants must be currently authorized to work in the United States on a fulltime basis without the need for employer support or sponsorship now or in the future
- Degree or equivalent and typically requires 4+ years of relevant experience
- Bachelor's degree in Computer Science, Software Engineering, Information Systems, Data Science, or a related field, or equivalent practical experience
- 4+ years of experience in data engineering, database engineering, software engineering, or a related technical discipline
- 3+ years of hands-on experience with SQL and relational database technologies
- 2+ years of experience with Python development and automation
- 2+ years of experience with Databricks, Spark, or modern cloud-based data engineering platforms
- Experience with Power BI and/or Tableau
- Experience working in Agile development environments
- Experience using GitHub and CI/CD processes
- Strong analytical, troubleshooting, and problem-solving capabilities
- Strong hands-on experience with **Databricks**, including Delta Lake and Apache Spark
- Advanced proficiency in **SQL** for complex queries, performance tuning, data modeling, and optimization
- Strong programming expertise in **Python** for automation, data processing, integration, and analytics
- Experience designing and maintaining enterprise-scale data pipelines and data processing frameworks
- Experience with workflow orchestration platforms such as **Databricks Workflows**, **Apache Airflow**, or equivalent technologies
- Experience developing dashboards, reports, and visualizations using **Power BI**
- Ability to transform business requirements into actionable reporting and analytics solutions
- Understanding of modern data warehousing, lakehouse architectures, and analytics best practices
- Strong knowledge of **GitHub-based** source control including branch protection policies, pull request reviews, release management, and version control best practices
- Experience implementing and maintaining **CI/CD pipelines** using **GitHub Actions** to automate build, testing, security validation, and deployment processes
- Familiarity with automated testing, deployment automation, and infrastructure best practices
- Experience working within **Agile** software development methodologies
- Understanding of healthcare data domains, including: + Clinical Data + Claims Data + Provider Data + Patient Data
- Familiarity with HIPAA and healthcare compliance requirements
- Understanding of healthcare data governance, privacy, and security best practices
- Experience leveraging AI development tools such as GitHub Copilot or equivalent solutions
- Ability to utilize AI for code generation, optimization, testing, documentation, and productivity improvements
- Exceptional problem-solving skills with the ability to troubleshoot and resolve complex technical and data-related challenges
- Strong ownership mentality with a focus on accountability and delivering results
- Naturally curious with a passion for continuous learning, innovation, and technology modernization
- Excellent communication and collaboration skills across technical and non-technical stakeholders
- Ability to work effectively in a fast-paced, data-driven, and highly collaborative environment
- Strong attention to detail and commitment to delivering high-quality solutions
- Demonstrates an enterprise mindset and a customer-first approach to decision-making
- If located in DFW area, the selected candidate may be expected to work on‑site at our Las Colinas office a minimum of two (2) days per week, with the remaining days worked remotely. Specific in‑office days may be designated according to team needs and business priorities
- * Experience working in Azure cloud environments
- * Familiarity with Databricks, Delta Lake, Lakehouse architectures, and modern data platform design
- * Experience supporting large-scale healthcare analytics platforms
- * Experience with healthcare interoperability standards such as HL7 or FHIR
- * Experience implementing data quality frameworks and data observability solutions
- * Experience supporting enterprise reporting modernization initiatives
- * Exposure to machine learning, predictive analytics, or AI-enabled healthcare solutions
Benefits
- Annual bonus may be offered.
- Long-term incentive opportunities may be offered.
- Possibility of a hybrid work arrangement, with at least two days per week on-site at the Las Colinas office for candidates located in the DFW area and the remaining days worked remotely.
Company Overview