McKesson

Data Engineer

Vaga remota de Data Engineering com fit claro de localização do candidato.

Publicada22 de jul. de 2026

Países elegíveis1 país aceito

Sinal de senioridadeSenior

Modelo de trabalhoRemoto

Locais aceitos para candidatos

Estados Unidos

Resumo da vaga

Conteúdo da vaga extraído em seções para revisão mais rápida.

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.

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.

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.

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.

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.

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