Finance Solutions, Google Cloud Platform

McKesson; Richmond (VA); On-site; USD 100,000 - 160,000; Full time

Benefits offered by this job

Hybrid work schedule

Job summary

McKesson is seeking a Data Engineer to join the Finance Data & BI organization, driving cloud-based data solutions in Google Cloud Platform (GCP). The role focuses on transforming financial data into analytics-ready assets to support reporting, forecasting, planning, and AI/ML initiatives.

The position is hybrid, based in Richmond, VA with monthly in-office requirements and relocation not offered. Ideal candidates have 4+ years of data engineering experience and a strong GCP background within an

Qualifications

• 4+ years of relevant experience as a Data Engineer.
• Hands-on experience delivering production-scale data engineering solutions in Google Cloud Platform (GCP).
• Experience with data warehouses, cloud platforms, relational databases, and BI tools.
• Strong proficiency in object-oriented programming languages such as Python, Java, or C#.

Responsibilities

• Solve complex problems across the full data stack, from data wrangling to production-scale solutions.
• Design architectures and reengineer data structures and databases.
• Develop, test, and maintain ETL/ELT pipelines using modern cloud technologies.
• Create and maintain database code and performance-optimized transformations.

Job description

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.

Are you a Data Engineer with hands‑on experience building modern data solutions in Google Cloud Platform (GCP) ? Do you want to play a leading role in a high‑visibility enterprise cloud transformation while helping shape the future of Finance Data at McKesson?

McKesson Medical‑Surgical (MMS) is seeking a highly skilled and motivated Data Engineer to join our Finance Solutions team. This is a critical individual contributor opportunity within our Finance Data & BI organization, where you will help lead the ongoing migration and modernization of our Finance data platforms to Google Cloud Platform (GCP) .

This role is ideal for data engineers who enjoy building scalable Finance data solutions within cloud environments and solving complex business challenges through modern data engineering practices. This position is embedded within the Finance Data & BI organization and focuses on transforming financial data into trusted, analytics-ready assets that support reporting, forecasting, planning, automation, AI/ML initiatives, and strategic business decision-making.

Reporting to the Director, Finance Data & BI, you will partner closely with Finance, Business Intelligence, Data Product, Architecture, and Data Science teams to design, build, and optimize modern cloud‑based Finance data solutions. Your work will directly influence the future‑state Finance data ecosystem and play a significant role in McKesson's strategic investment in Google Cloud Platform .

Important: We are specifically seeking Data Engineers with experience designing, building, and supporting cloud‑based data solutions, preferably within Google Cloud Platform (GCP) environments.

Hybrid Expectations

This position is based in Richmond, VA with 3 to 5 days in the office each month.

Preferred candidates must currently reside within a reasonable commuting distance (defined as within 60 miles of Richmond).

Relocation assistance is not available for this role.

Minimum Requirements

• 4+ years of relevant experience

Targeted Experience & Critical Skills

• 4+ years of technical and professional experience as a Data Engineer.
• Demonstrated hands‑on experience delivering production‑scale data engineering solutions within Google Cloud Platform (GCP). While we are open to candidates with as little as 2+ years of GCP experience, this capability is considered highly critical to success in the role. The selected candidate will play a significant role in accelerating the migration and modernization of Finance data platforms to GCP. Candidates with proven GCP experience will be strongly preferred.
• 4+ years of hands‑on experience with data warehouse solutions, cloud platforms, relational databases, and data visualization or dashboarding tools.
• 4+ years of experience working with structured and unstructured data in batch and real‑time data processing environments.
• Strong proficiency in object‑oriented programming languages such as Python, Java, or C# .

Proven experience in an enterprise environment with:

• Building and optimizing cloud‑based data solutions
• Supporting business‑critical systems
• Designing or supporting production‑scale AI/ML data pipelines
• Applying data governance by design
• Data warehousing and ETL best practices
• CI/CD and version control using GitHub

Additional Skills: (Nice to Have)

• Experience with PySpark
• Experience with Matillion or other modern ETL tools
• Working knowledge of core financial data concepts (general ledger, chart of accounts, financial reporting)
• Experience deploying SOX‑compliant data solutions in a regulated enterprise
• Experience with Oracle JD Edwards or familiarity with financial application data integrations and data flows

Key Responsibilities

Data Engineering & Architecture

• Solve complex problems across the full data stack, from advanced data wrangling (SQL, Python, Spark, or similar) to delivering stakeholder‑ready, production‑scale data solutions
• Design new architectures and reengineer existing ones, including optimized data structures, relational databases, and database code
• Develop, construct, test, and maintain robust, scalable, and efficient ETL/ELT pipelines using modern cloud technologies that support advanced analytics and AI/ML workloads
• Develop and maintain database code, including stored procedures, functions, and performance‑optimized transformations
• Create and maintain ETL processes and contri