We are seeking a motivated Entry-Level Integration Developer / Data Engineer to help design, build, and maintain the integration backbone of our enterprise data ecosystem. In this role, you’ll work hands-on with our ETL platform, creating and optimizing integration solutions that connect diverse applications and data sources across our network — including APIs, message queues, and databases.

You’ll collaborate within a small, agile engineering team supporting on-premise and air-gapped control network environments, ensuring reliable, secure, and efficient data movement. This position offers an excellent opportunity to gain deep, practical experience in modern data integration and middleware technologies while contributing to mission-critical systems.

Key Responsibilities

Design, develop, and maintain ETL and integration workflows to support data movement and system interoperability.
Configure connectors and adapters for APIs, message queues (MQs), and various data sources.
Implement data transformations and business logic to enable seamless integration across applications.
Support and troubleshoot integration processes to ensure stability, performance, and data accuracy.
Collaborate with engineers and stakeholders to enhance integration design, deployment, and automation practices.

Required Qualifications

Bachelor’s degree in Computer Science, Computer Engineering, or a related technical field.
Foundational understanding of ETL concepts, pipelines, and data transformation principles.
Basic programming knowledge in Java or Kotlin.
Familiarity with infrastructure fundamentals such as network routing, authentication (authN), and authorization (authZ).
Strong analytical, troubleshooting, and problem-solving skills with attention to detail.

Preferred Qualifications

1+ years of hands-on experience (academic, lab, or professional) with any ETL or middleware platform.
Practical experience developing in Java or Kotlin using IntelliJ IDEA or similar IDEs.
Basic understanding of containers and Kubernetes orchestration.
Exposure to commonly used data source technologies, including:
Kafka (streaming and messaging)
Oracle and PostgreSQL databases
JMS and IBM MQ integration technologies

Apt

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