Finance Data Engineer, GCP Cloud & Analytics

McKesson; Richmond (VA); Hybrid; USD 107,000 - 178,000; Full time

Job summary

McKesson is seeking a Data Engineer for Finance Solutions to drive the migration and modernization of Finance data platforms to Google Cloud Platform (GCP). The role is based in Richmond, VA with 3–5 days in office monthly, remote flexibility not specified, and a focus on production-scale data solutions for analytics, forecasting, and AI/ML initiatives.

The candidate will partner with Finance, BI, Data Product, and Architecture teams to design, build, and optimize cloud-based Finance data

Qualifications

• 4+ years of relevant experience in data engineering.
• Hands-on experience delivering production-scale data solutions in GCP.
• 4+ years in data warehousing, cloud platforms, databases, and BI tooling.
• 4+ years handling structured and unstructured data in batch and real-time contexts.
• Proficiency in Python, Java, or C# for data pipelines.
• Experience with CI/CD and GitHub for deployment workflows.

Responsibilities

• Solve complex problems across the full data stack with production-scale solutions.
• Design and reengineer architectures, optimize data structures and databases.
• Develop and maintain scalable ETL/ELT pipelines using cloud tech.
• Create and maintain database code and performance-optimized transformations.
• Build CI/CD processes and contribute to GitHub Actions workflows.

Skills

Data engineering

GCP experience

Data warehousing

Batch & real-time processing

Python/Java/C#

CI/CD with GitHub

SQL / Spark

Data governance

Tools

PySpark

Matillion

Oracle JD Edwards

Job description

McKesson is seeking a Data Engineer for Finance Solutions to drive the migration and modernization of Finance data platforms to Google Cloud Platform (GCP). The role is based in Richmond, VA with 3–5 days in office monthly, remote flexibility not specified, and a focus on production-scale data solutions for analytics, forecasting, and AI/ML initiatives.

The candidate will partner with Finance, BI, Data Product, and Architecture teams to design, build, and optimize cloud-based Finance data