Data Engineer

What Data Engineering Contributes to Cardinal Health

The Data & Analytics Function oversees the analytics lifecycle to identify, analyze, and present actionable insights that drive business decisions and create competitive advantage. This function manages enterprise data platforms, data access, governance, reporting, business intelligence solutions, and advanced analytics capabilities.

Data Engineering is responsible for building, maintaining, and optimizing scalable data platforms that enable efficient data ingestion, transformation, orchestration, and consumption across the enterprise. As part of the Platform Engineering team, this role focuses on delivering reliable, secure, automated, and scalable data infrastructure supporting business-critical analytics and data products.

The ideal candidate will contribute to platform operations, cloud-based data engineering solutions, CI/CD automation, and production support while partnering with cross-functional teams to ensure a stable and high-performing data ecosystem.

Qualifications

3-5 years of experience in Data Engineering, Platform Engineering, Site Reliability Engineering (SRE), DevOps, or related technical roles.

2-4 years of experience in Data Engineering, Platform Engineering, Cloud Engineering, SRE, or DevOps.

Bachelor’s degree in computer science, Engineering, Information Systems, or a related discipline.

Strong hands-on experience with Databricks and Apache Spark is required.

Experience with Azure, AWS, or GCP cloud platforms is required.

Experience building and maintaining CI/CD pipelines using Harness, Azure DevOps, GitHub Actions, or similar tools is required.

Strong experience with SQL, Python, and PySpark.

Hands-on experience with Git/GitHub and source control best practices is required.

Experience supporting production environments and platform operations.

Understanding of Infrastructure as Code concepts (Terraform preferred).

Familiarity with monitoring, observability, security, and governance practices.

Key Responsibilities

Support and enhance Databricks-based enterprise data platform solutions.

Develop, deploy, and optimize data processing workloads using Databricks and Spark.

Build and manage CI/CD pipelines to automate deployment and platform operations.

Monitor platform performance, reliability, and availability.

Investigate and resolve platform incidents, deployment failures, and operational issues.

Contribute to platform modernization, automation, and cloud optimization initiatives.

Collaborate with Data Engineers, Architects, and Product teams to deliver scalable platform capabilities.

Support governance, security, and operational compliance requirements.

Create and maintain technical documentation and operational procedures.

What Is Expected of You and Others at This Level

Works independently on moderately complex assignments.

Demonstrates strong troubleshooting and analytical capabilities.

Contributes to platform reliability and operational improvement initiatives.

Supports automation and DevOps adoption across platform engineering processes.

Partners effectively with cross-functional teams and stakeholders.

Takes ownership of assigned deliverables and operational outcomes.

Preferred Technical Skills

• Databricks (Workflows, Delta Lake, Unity Catalog)
• Apache Spark / PySpark
• Harness CI/CD Pipelines
• Python
• SQL
• Azure Data Platform, GCP, or AWS
• Git/GitHub
• Terraform
• Monitoring and Observability Tools
• DevOps & Platform Engineering Practices
• Incident and Production Support Management

Work Schedule

This role is part of the global Data Engineering Platform Operations team and requires participation in a rotational shift schedule to ensure support coverage across multiple regions and time zones. Team members will also be required to provide weekend support on a rotational basis, approximately one weekend per month. A compensatory day off will be provided for weekend support.

Candidates should be comfortable working in the following shifts based on business requirements:

• Morning Shift: 7:00 AM - 3:00 PM
• Afternoon Shift: 1:00 PM - 10:00 PM
• Evening Shift: 5:30 PM - 2:30 AM

The shift schedule may vary depending on operational and business needs.

Additional Expectations

• Participate in rotational production support and platform operations activities.
• Monitor and support Databricks environments, data pipelines, CI/CD deployments, and platform services.
• Respond to platform incidents, service disruptions, deployment failures, and operational requests within defined SLAs.
• Collaborate effectively with globally distributed platforms, engineering, and business teams.