Data Engineer

McKesson•Columbus, OH

1d•$106,500 - $177,500

About The Position

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. We foster a culture where you can grow, make an impact, and are empowered to bring new ideas. CoverMyMeds is seeking a Specialist, Data Engineering to join our Data Engineering team. Our Data Engineering Team is a highly technical group of results driven Engineers, Analysts and Architects focused on providing our internal and external clients with high quality, repeatable and scalable data solutions. This role focuses on building and maintaining reliable data integrations, transforming complex data into trusted business assets, and supporting analytics and reporting initiatives across the organization. The ideal candidate brings strong Databricks expertise, experience working with large-scale datasets, and the ability to partner effectively with business and technical stakeholders. This individual will help deliver high-quality data solutions while contributing to a collaborative team environment and supporting the growth of junior team members.

Requirements

Bachelor's degree in Computer Science, Information Systems, or related field, or equivalent experience.
4+ years of experience in a dedicated Data Engineering role.
4+ years of hands-on experience building and supporting data pipelines and data integration solutions.
Strong experience with Databricks in a production environment.
Strong SQL development skills.
Experience working with Azure-based data services.
Experience supporting reporting, analytics, systems integration, and data governance initiatives.
Demonstrated expertise in conceptual and logical data modeling.
Experience working with both structured and unstructured data.
Strong written and verbal communication skills.

Nice To Haves

Experience with data streaming and event-driven architectures such as Kafka.
Experience with Infrastructure as Code tools such as Terraform.
Experience supporting large-scale cloud migration or modernization programs.
Familiarity with AI-assisted development tools such as Claude Code, GitHub Copilot, or similar technologies.
Experience supporting business-critical applications and highly available data platforms.
Experience mentoring junior engineers or providing technical guidance within a collaborative team environment.

Responsibilities

Design, build, and maintain scalable data pipelines that support reporting, analytics, and operational business needs.
Develop data ingestion and integration processes from a variety of structured and unstructured data sources.
Create and optimize data transformations using SQL, Databricks, and Azure-based technologies.
Support both batch and real-time data processing solutions.
Implement data quality, validation, and monitoring processes to ensure trusted and reliable data assets.
Troubleshoot and resolve data pipeline performance, reliability, and data quality issues.
Develop conceptual and logical data models based on business reporting requirements.
Partner with business stakeholders, analysts, and technology teams to understand data needs and translate them into scalable solutions.
Work with application development teams to understand source systems and build efficient data flows into enterprise data environments.
Support data governance initiatives through standardization, documentation, and quality controls.
Partner closely with Data Systems Analysts, Analytics teams, and Technology partners to solve business problems with data.
Communicate technical concepts clearly to both technical and non-technical audiences.
Leverage modern engineering practices and AI-assisted development tools to improve solution delivery and efficiency.
Share knowledge and provide guidance to less experienced team members.