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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 highquality analyticsready and AIenabled 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 futurestate 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.

Compensation

• Base: $130000 to $140000

• 10% Annual Incentive

Key Responsibilities

Data Engineering & Architecture

• Solve complex problems across the full data stack from advanced data wrangling (SQL Python Spark or similar) to delivering stakeholderready productionscale 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 performanceoptimized 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 nontechnical stakeholders balancing innovation with operational risk and controls

• Enable trusted data environments required for forecasting models scenario planning and AIdriven 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 handson 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 realtime data processing environments

• Strong proficiency in objectoriented 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 cloudbased data solutions

  • Supporting businesscritical systems

  • Designing or supporting productionscale 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 SOXcompliant data solutions in a regulated enterprise

• Experience with Oracle JD Edwards or familiarity with financial application data integrations and data flows

We are proud to offer a competitive compensation package at McKesson as part of our Total Rewards. This is determined by several factors including performance experience and skills equity regular job market evaluations and geographical markets. The pay range shown below is aligned with McKessons pay philosophy and pay will always be compliant with any applicable regulations. In addition to base pay other compensation such as an annual bonus or long-term incentive opportunities may be offered. For more information regarding benefits at McKesson pleaseclick here.

Our Base Pay Range for this position

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