Data Engineer

CoverMyMeds • Columbus, OH

10d

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. Here, we focus on the health, happiness, and well-being of you and those we serve – we care. What you do at McKesson matters. We foster a culture where you can grow, make an impact, and are empowered to bring new ideas. Together, we thrive as we shape the future of health for patients, our communities, and our people. If you want to be part of tomorrow’s health today, we want to hear from you. CoverMyMeds’ Data & Analytics is looking for a Specialist, Data Engineering to join our Data Engineering team. Of note, 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. Together with our various business units, the work our Data Engineering team does ultimately helps get more people the medicine they need to live healthier lives. What You’ll Do The Specialist, Data Engineering will support and expand the data platforms that power our commercial data products and analytics offerings. This role will contribute to the design and delivery of scalable, reusable data assets that enable both internal teams and external partners to derive value from our data. You will work across proprietary and third-party data sources to build well-structured, high-quality datasets, prototypes, and sample data assets that support commercialization efforts. This role partners closely with Data Systems Analysts, Product, and Analytics teams to translate evolving business concepts into tangible, testable data solutions. Position Description Design and develop data solutions that integrate proprietary and third-party data sources to support commercial data products and proof-of-concept initiatives. Build and optimize data ingestion and transformation pipelines that enable rapid iteration while maintaining quality and governance standards. Work with structured and unstructured data to prepare enhanced, sample, or prototype datasets for internal stakeholders and potential external customers. Write SQL and/or use cloud-based tools such as Snowflake or Databricks to cleanse, standardize, and enrich data aligned to defined business use cases. Collaborate with Product, Analytics, and external-facing teams to translate commercialization objectives into scalable data assets. Contribute to conceptual data models and reusable data patterns that support future data product expansion. Partner with application and platform teams to understand upstream data flows and design appropriate ingestion strategies. Support monitoring of data quality, performance, and reliability for commercialized data assets. Priority will be given to candidates who reside in the Columbus, OH metropolitan area. We are unable to provide sponsorship for this role presently, or in the future.

Requirements

• Degree or equivalent and typically requires 4+ years of relevant experience
• Bachelor’s degree in Computer Science, Information Systems, or related field
• 4+ years of experience in data engineering, analytics engineering, or modern data platform environments
• 4+ years h ands-on experience with cloud data technologies such as Snowflake, Databricks, or similar platforms
• Strong ( 4+ years) SQL skills and experience transforming data for analytical, reporting, or product-oriented use cases
• Experience integrating data from multiple internal and third-party systems
• Experience working with structured and semi-structured data in batch and/or streaming environments
• Working knowledge of data modeling principles and data quality practices
• Experience supporting analytics, reporting, or externally facing data use cases

Nice To Haves

• Experience with or interest in data commercialization, data products, or externally facing analytics solutions
• Experience building prototype or proof-of-concept data assets, or interest in working in rapid iteration environments
• Comfort working with evolving requirements and ambiguity
• Ability to translate loosely defined business ideas into structured data outputs
• Strong collaboration skills across product, analytics, and technical teams
• Ownership mindset with a bias toward execution

Responsibilities

• Design and develop data solutions that integrate proprietary and third-party data sources to support commercial data products and proof-of-concept initiatives.
• Build and optimize data ingestion and transformation pipelines that enable rapid iteration while maintaining quality and governance standards.
• Work with structured and unstructured data to prepare enhanced, sample, or prototype datasets for internal stakeholders and potential external customers.
• Write SQL and/or use cloud-based tools such as Snowflake or Databricks to cleanse, standardize, and enrich data aligned to defined business use cases.
• Collaborate with Product, Analytics, and external-facing teams to translate commercialization objectives into scalable data assets.
• Contribute to conceptual data models and reusable data patterns that support future data product expansion.
• Partner with application and platform teams to understand upstream data flows and design appropriate ingestion strategies.
• Support monitoring of data quality, performance, and reliability for commercialized data assets.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level