Data Engineer

What You’ll Do Data Engineering & Pipeline Development Design, build, and maintain scalable data pipelines that support reporting, analytics, and operational business needs. Develop data ingestion and integration processes from a variety of structured and unstructured data sources. Create and optimize data transformations using SQL, Databricks, and Azure-based technologies. Support both batch and real-time data processing solutions. Implement data quality, validation, and monitoring processes to ensure trusted and reliable data assets. Troubleshoot and resolve data pipeline performance, reliability, and data quality issues. Data Modeling & Business Support Develop conceptual and logical data models based on business reporting requirements. Partner with business stakeholders, analysts, and technology teams to understand data needs and translate them into scalable solutions. Work with application development teams to understand source systems and build efficient data flows into enterprise data environments. Support data governance initiatives through standardization, documentation, and quality controls. Team Collaboration Partner closely with Data Systems Analysts, Analytics teams, and Technology partners to solve business problems with data. Communicate technical concepts clearly to both technical and non-technical audiences. Leverage modern engineering practices and AI-assisted development tools to improve solution delivery and efficiency. Share knowledge and provide guidance to less experienced team members. Minimum Qualifications Bachelor’s degree in Computer Science, Information Systems, or related field, or equivalent experience. 4+ years of experience in a dedicated Data Engineering role. 4+ years of hands‑on experience building and supporting data pipelines and data integration solutions. Strong experience with Databricks in a production environment. Strong SQL development skills. Experience working with Azure-based data services. Experience supporting reporting, analytics, systems integration, and data governance initiatives. Demonstrated expertise in conceptual and logical data modeling. Experience working with both structured and unstructured data. Strong written and verbal communication skills. Preferred Qualifications Experience with data streaming and event‑driven architectures such as Kafka. Experience with Infrastructure as Code tools such as Terraform. Experience supporting large‑scale cloud migration or modernization programs. Familiarity with AI‑assisted development tools such as Claude Code, GitHub Copilot, or similar technologies. Experience supporting business‑critical applications and highly available data platforms. Experience mentoring junior engineers or providing technical guidance within a collaborative team environment. Compensation and Benefits Base Pay Range: $106,500 - $177,500. 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, please refer to the company's benefits page. Equal Opportunity Employer McKesson is an Equal Opportunity Employer and provides equal employment opportunities to applicants and employees, without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, age, genetic information, or any other legally protected category. #J-18808-Ljbffr McKesson’s Corporate