Senior Data Engineer — AWS, Kafka Pipelines (Remote)

Argyllinfotech; Dallas (TX); Hybrid; USD 69,000 - 76,000; Full time

Job summary

Centene is seeking a Senior Data Engineer to design and build cloud-native data pipelines using AWS, Kafka, Python, and Java. You will contribute to the PISCES HUB platform, delivering scalable, configurable, event-driven processing and data integration services.

Responsibilities include building and optimizing AWS-based pipelines, designing metadata-driven workflows, and implementing robust testing, observability, and CI/CD integration using Docker/Kubernetes and Dynatrace.

Qualifications

• 7+ years in software engineering and application development.
• 4+ years building AWS-based solutions, Kafka integrations, and data pipelines.
• Experience designing distributed, cloud-native applications.

Responsibilities

• Design, develop, and maintain scalable components for the PISCES HUB platform.
• Build AWS-based data pipelines, event-driven workflows, APIs, microservices, and integration services.
• Develop Kafka producers and consumers, including topic/partition/schema management and error handling.
• Design configuration-driven systems including metadata-driven pipelines, dynamic business rules, and configurable APIs.
• Implement JSON/YAML/XML configuration interpreters and ensure validation, versioning, and rollback.
• Develop Python and/or Java code with robust testing and CI/CD integration.
• Collaborate with architects, product owners, QA, data engineers, and DevOps.

Skills

Python

Java

AWS

Kafka

Data pipelines

Docker

Kubernetes

SQL/NoSQL

Education

Bachelors in CS or related

Tools

Docker

Kubernetes

AWS

Git

Job description

Centene is seeking a Senior Data Engineer to design and build cloud-native data pipelines using AWS, Kafka, Python, and Java. You will contribute to the PISCES HUB platform, delivering scalable, configurable, event-driven processing and data integration services.

Responsibilities include building and optimizing AWS-based pipelines, designing metadata-driven workflows, and implementing robust testing, observability, and CI/CD integration using Docker/Kubernetes and Dynatrace.