Data Engineer, Finance Data & BI

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 contribute to CI/CD deployment workflows using GitHub Actions or similar tools
• Optimization, Data Quality & Governance
• 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
• Collaboration & Communication
• 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
• Minimum Requirements
• 4+ years of relevant experience
• Preferred Critical Requirements
• 4+ years of technical and professional experience as a Data Engineer
• 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#
• Demonstrated experience with Google Cloud Platform (GCP) preferred over other platforms (e.g., Snowflake, Databricks, Microsoft, Teradata)
• 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 regulat

Benefits

Additional Information

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. McKesson Medical-Surgical (MMS) is seeking a highly skilled and motivated Data Engineer to join the Finance Solutions team. This is a critical individual contributor role within our Finance Data & BI organization. The Data Engineer will design, build, and optimize scalable data pipelines and architectures that transform raw financial data into high‑quality, analytics‑ready, and AI‑enabled datasets . These datasets support strategic reporting, planning, forecasting, automation, and advanced analytics across the organization. Reporting to the Director, Finance Data & BI , this Data Engineer will serve as an agile technical partner to Data Product, Architecture, Business Intelligence, Data Science, Finance Analysts, and business stakeholders. This role plays a key part in building the future‑state Finance data platforms at MMS, supporting enterprise analytics, AI/ML use cases, and sound financial governance. 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.

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