Finance Solutions, Google Cloud Platform

McKesson • Richmond, VA

22h • $106,500 - $177,500 • Hybrid

About The Position

McKesson is seeking a highly skilled and motivated Data Engineer to join their Finance Solutions team. This is a critical individual contributor opportunity within the Finance Data & BI organization, focused on leading the ongoing migration and modernization of Finance data platforms to Google Cloud Platform (GCP). The 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. The 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, the Data Engineer 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. The work will directly influence the future-state Finance data ecosystem and play a significant role in McKesson's strategic investment in Google Cloud Platform. McKesson Medical-Surgical (MMS), which is expected to become Wellverse in early 2027, is a subsidiary and publicly reported segment of the McKesson Corporation. MMS distributes medical-surgical supplies, pharmaceuticals, diagnostic equipment and supplies, along with other solutions and services to virtually every type of healthcare setting and provider outside of the traditional hospital. Alternate Care markets are growing rapidly and MMS is proud to be a leader in this space. With a team of approximately 8,000 employees, a network of 15 distribution centers and approximately 900 delivery vehicles, they collaborate with more than 2,200 leading manufacturers and serve over 200,000 customer accounts across the U.S. Their catalog includes more than 270,000 SKUs of branded and private-label medical-surgical products.

Requirements

• 4+ years of relevant experience
• 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).
• 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

Nice To Haves

• 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

Responsibilities

• 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 contribute to CI/CD deployment workflows using GitHub Actions or similar tools
• Implement and optimize data models (e.g., dimensional modeling) within the Finance data environment
• Optimize data architecture for performance, scalability, and cost efficiency across large financial datasets
• Design and implement automated data quality checks, anomaly detection, and validation processes to ensure accuracy and trust in downstream analytics and AI use cases
• Ensure all data solutions meet financial governance and compliance standards, including SOX requirements
• Partner closely with Finance teams (Accounting, FP&A), BI, and Data Product partners to translate complex business requirements into scalable technical solutions
• Communicate technical concepts clearly to non‑technical stakeholders, balancing innovation with operational risk and controls
• Enable trusted data environments required for forecasting models, scenario planning, and AI‑driven insights
• Contribute to the strategic evolution of the Finance data platform by evaluating and piloting emerging tools and technologies

Benefits

• competitive compensation package
• Total Rewards
• annual bonus
• long-term incentive opportunities

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed