Data Engineer

McKesson•Irving, TX

12d•$157,414 - $168,600•Remote

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.

Requirements

Bachelor’s degree, or foreign equivalent, in Computer Science, Computer Engineering or a related field and five (5) years of experience in the job offered or related field.
Two (2) years demonstrated experience in SQL to debug and fix application related issues.
Two (2) years demonstrated experience in Java to build new and enhance existing application.
Two (2) years demonstrated experience in Python to build new and enhance existing application.
Two (2) years demonstrated experience in MySQL to write queries to investigate and fix data issues associated to application.
Two (2) years demonstrated experience in Databricks to build and maintain scalable data pipelines for application data processing and analytics.
Two (2) years demonstrated experience in Amazon S3 to manage application data storage, retrieval, and integration with data processing workflows.
Two (2) years demonstrated experience in GitLab to version control application code and collaborate on development and deployment activities.
Two (2) years demonstrated experience in API calls to integrate external services and troubleshoot application functionality and data flow.
Two (2) years demonstrated experience in Katalon to automate application testing and validate functionality across different environments.

Responsibilities

Independently design, develop, and maintain scalable, high performance data pipelines and data platforms.
Analyze business and technical requirements to design end to end data solutions, including data ingestion, transformation, data modeling, and data serving layers.
Lead the design and implementation of complex ETL/ELT workflows, optimizing for performance, reliability, and cost efficiency.
Implement advanced Delta Lake capabilities such as schema enforcement, schema evolution, and data versioning.
Collaborate closely with Product, QA, and upstream system owners to finalize data contracts, define SLAs, and ensure reliable and timely data delivery.
Debug complex data issues involving distributed processing, increasing data volumes, latency challenges, and upstream system changes.
Enforce data governance, security, and compliance standards within Databricks, including access controls and cataloging solutions.
Participate in design and code reviews, identify systemic issues, and propose improvements to data pipelines, orchestration, deployment, and observability.
Mentor junior engineers and contribute to team knowledge sharing.