Data Engineering Analyst

Cardinal Health

. Support the design, implementation, and maintenance of enterprise data platform solutions .

Posted 11/3/2026full-timeUnited StatesJuniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and managing data processing workloads using Databricks and Apache Spark, while ensuring adherence to security and compliance standards. Proficient in CI/CD pipeline development and operational support, with a focus on automation and platform reliability.

Highest-signal resume keywords

DatabricksApache SparkCI/CD Pipeline DevelopmentMicrosoft AzureData Engineering

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

SQLPythonPySparkInfrastructure as CodeTerraformData ProcessingPlatform MonitoringIncident ManagementCloud-Based Data PlatformsData Governance

Soft Skills

CollaborationProblem-SolvingCommunication

Tools & Technologies

HarnessAzure DevOpsGitHub ActionsGoogle Cloud PlatformAWS

Industry Keywords

Data EngineeringPlatform EngineeringSite Reliability EngineeringDevOpsOperational Standards

Tech Stack

Tools & technologies

ApacheAWSAzureCloudGoogle Cloud PlatformPySparkPythonSparkSQLTerraform

About the role

Key responsibilities & impact

Support the design, implementation, and maintenance of enterprise data platform solutions
Develop, deploy, and manage data processing workloads using Databricks and Apache Spark
Build and maintain CI/CD deployment pipelines using Harness and other DevOps tools
Support platform modernization, cloud migration, automation, and continuous improvement initiatives
Monitor platform health, performance, and availability and identify optimization opportunities
Investigate and resolve platform issues, deployment failures, and data pipeline incidents
Collaborate with Data Engineers, Architects, Product Teams, and Business Stakeholders
Ensure adherence to security, compliance, governance, and operational standards
Participate in production support, root cause analysis, and incident resolution
Contribute to documentation, operational runbooks, and knowledge-sharing initiatives
Work with global teams to deliver highly available and scalable platform services
Monitor and support Databricks environments, data pipelines, CI/CD deployments, and platform services
Support continuous improvement focused on automation, reliability, and operational efficiency

Requirements

What you’ll need

1-3 years of experience in Data Engineering, Platform Engineering, Site Reliability Engineering (SRE), DevOps, or related technical roles
Bachelor’s degree in computer science, Engineering, Information Systems, or a related discipline, or equivalent work experience
Hands-on experience with Databricks, Apache Spark, and cloud-based data platforms
Experience developing, maintaining, and supporting CI/CD pipelines using Harness, Azure DevOps, GitHub Actions, or similar tools
Working knowledge of Microsoft Azure, Google Cloud Platform (GCP), or AWS
Experience with SQL, Python, PySpark, and data engineering best practices
Familiarity with Git/GitHub
Basic understanding of Infrastructure as Code (IaC), preferably Terraform
Knowledge of platform monitoring, observability, incident management, and operational support processes
Understanding of data governance, security, access management, and platform reliability principles
Comfortable working rotational shifts: 6:00 AM - 3:00 PM, 1:00 PM - 10:00 PM, or 5:30 PM - 2:30 AM
Ability to participate in rotational production support and platform operations activities
Ability to respond to incidents, service disruptions, deployment failures, and operational requests within defined SLAs
Ability to collaborate with globally distributed teams

Benefits

Comp & perks

Inclusive workplace valuing diversity of thought, experience, and background
Equal Opportunity employer
Rotational shift model providing support coverage across multiple regions and time zones