Integration Engineer

Location: Salt Lake City, UT Salary: $55.00 USD Hourly - $58.00 USD Hourly Description:
Integration Engineer

Location: Salt Lake City, UT
Work Model: Onsite
Employment Type: Contract-to-Hire (6+ Month Contract with Potential for Full-Time Conversion)
About the Role

As an Integration Engineer, you will help build and modernize the integration services that power a connected enterprise. You will design, develop, and support scalable APIs, event-driven platforms, and cloud-native integration solutions that enable secure communication between applications, data platforms, and business systems.

You will work with modern technologies including Python, Apache Kafka, Docker, Kubernetes, REST APIs, and CI/CD automation while collaborating across engineering, cloud, data, infrastructure, and security teams. This role is ideal for an engineer who enjoys solving complex integration challenges, implementing API security best practices, and driving modernization initiatives through automation and emerging technologies.
What You'll Do

• Design, develop, test, deploy, and maintain enterprise integration services, middleware solutions, and REST APIs using Python and modern integration patterns.
• Build secure API ecosystems by implementing authentication, authorization, OAuth 2.0, JWT, JWE, HMAC, and service-to-service security frameworks.
• Develop and support Kafka-based event-driven architectures, including producers, consumers, topic management, resiliency, and message processing.
• Create and manage containerized integration services using Docker and Kubernetes while applying cloud-native and microservices best practices.
• Design and optimize CI/CD pipelines, automated testing frameworks, source control processes, and release automation workflows.
• Implement integrations using REST/JSON, SOAP, XML, XSD, and WSDL across enterprise platforms and applications.
• Work with API management and middleware technologies, including Apigee Edge/Hybrid and IBM App Connect Enterprise (ACE).
• Monitor, troubleshoot, and optimize production integration services, performing root cause analysis and driving reliability improvements.
• Collaborate with application development, cloud, security, architecture, and data teams throughout the software development lifecycle.
• Evaluate and leverage emerging technologies, including AI-assisted development tools, GitHub Copilot, Databricks, and Data-as-a-Service (DaaS) capabilities.
• Contribute to reusable integration frameworks, engineering standards, automation initiatives, and technical documentation.

Minimum Qualifications

• Bachelor's degree in Computer Science, Engineering, Information Technology, or a related field, or equivalent practical experience.
• Experience developing enterprise-grade applications and integration services using Python.
• Experience designing, developing, and supporting REST APIs and JSON-based integrations.
• Experience implementing API security standards, including OAuth 2.0, JWT, authentication, authorization, and secure communication protocols.
• Experience with Apache Kafka and event-driven architecture patterns.
• Experience developing and deploying containerized applications using Docker and Kubernetes.
• Experience with CI/CD pipelines, DevOps methodologies, Git, automated testing, and release automation.
• Experience working in Agile or SAFe software development environments.
• Strong troubleshooting, analytical, and production support experience.
• Excellent communication and collaboration skills.

Preferred Qualifications

• Experience with Apigee Edge, Apigee Hybrid, or other enterprise API management platforms.
• Experience with IBM App Connect Enterprise (ACE) or similar middleware/integration platforms.
• Knowledge of SOAP, XML, XSD, and WSDL technologies.
• Experience with Databricks and modern data integration architectures.
• Experience with API governance, lifecycle management, reusable integration frameworks, and enterprise API standards.
• Experience with Behavior-Driven Development (BDD) and automated testing practices.
• Knowledge of monitoring, observability, performance optimization, and distributed systems reliability.
• Experience using AI/GenAI-enabled development tools, including GitHub Copilot.

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