Senior Kafka & Data Integration Analyst

Cardinal Health, Inc.; Dublin (OH); On-site; USD 81,000 - 115,000; Full time

Benefits offered by this job

Medical, dental and vision coverage

401k savings plan

Paid time off

HSA

Job summary

Cardinal Health, Inc. is seeking a Software & Information Platforms professional to validate data-driven hypotheses, design and implement event-driven systems, and collaborate with multiple teams to resolve complex issues.

The role involves developing Kafka producers/consumers with Java or Python, and building integrations via Kafka Connect. The position emphasizes problem-solving, communication of options, and understanding how data workflows impact downstream processes.

Qualifications

• 2-4 years of experience preferred.
• Bachelor's degree in related field preferred, or equivalent work experience.

Responsibilities

• Validates hypotheses with data and proposes fixes.
• Analyzes why issues occur, assesses impacts, and proposes options.
• Collaborates across apps, platforms, and SRE teams to resolve complex issues and prevent recurrences.
• Communicates recommended options (risk/effort/impact) to leads for decision making.
• Develop and maintain Kafka producers and consumers using Java, Python, or similar technologies.
• Assist in designing and implementing event-driven applications.
• Create and maintain Kafka topics, consumer groups, and message schemas.
• Develop integrations using Kafka Connect source and sink connectors.

Education

Bachelor's degree in related field preferred, or equivalent work experience

Tools

Kafka

Kafka Connect

Java

Python

Job description

Cardinal Health, Inc. is seeking a Software & Information Platforms professional to validate data-driven hypotheses, design and implement event-driven systems, and collaborate with multiple teams to resolve complex issues.

The role involves developing Kafka producers/consumers with Java or Python, and building integrations via Kafka Connect. The position emphasizes problem-solving, communication of options, and understanding how data workflows impact downstream processes.