Avensys Consulting
Senior Java & Kafka Developer
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Role: Senior Java & Kafka Developer (2 roles); Lead (1 Role)
Location: London (3 days onsite)
Type: Contract – Outside IR35
Design and deliver secure, scalable tech products for Bank, leveraging Java, Kafka, and various databases. Key responsibilities include developing and maintaining production code, troubleshooting, data analysis, and driving system improvements.
Experience Required:
- Java 8+
- Spring Framework
- Kafka
- Oracle/MySQL
Must be capable of operating in an agile environment.
Hands-on Practical Experience:
- System Design
- Application Development
- Testing
- Operational Stability
Technical Skills:
- Core Java / Design Patterns
- Java 8 +
- Multi-threading
- Exception Handling
- Defensive Programming
- Microservices
- Java Design Patterns
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Software Frameworks
- Spring Core Framework
- Spring Boot
- Spring Integration
- Apache Camel
- Log4j 2.x / Logback
-
Testing Frameworks
- JUnit
- Powermock / Mockito
- Cucumber
- Mutation Testing
- Selenium
-
Messaging Protocols
- Kafka
- IBM MQ
- Active MQ
- RESTful HTTP
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Database
- Oracle
- MySQL
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Distributed Cache
- Hazelcast
- Redis
- Memcached
- Gemfire
Development Experience:
- Developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages.
- Overall knowledge of the Software Development Life Cycle.
- Solid understanding of agile methodologies such as CI/CD, Application Resiliency, and Security.
Additional Knowledge:
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- Demonstrated knowledge of software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.).
- Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security.
- Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices.
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