Notre client :
Our client is a technology-driven product company focused on developing scalable solutions for data-intensive systems. The team works on building and supporting distributed architectures for real-time data processing, ensuring efficient handling of large-scale data flows in production.
Vos tâches :
- Design and develop event-driven architecture based on Kafka
- Build and maintain real-time stream processing applications using Kafka Streams
- Design and develop ELK pipelines, indexes, dashboards, and alerting systems
- Lead and contribute to architecture discussions for event streaming solutions
- Configure and manage Kafka connectors and Kafka topics
- Develop efficient event-based data processing solutions according to design specifications
- Collaborate with development and QA teams across the full software development lifecycle
- Ensure performance, scalability, and reliability of data streaming systems
Expérience et compétences requises :
- 2+ years of experience developing Kafka-based applications
- 2+ years of experience with the following Kafka components: Kafka Streams (including Processor API), Kafka Connect, and Schema Registry
- 2+ years of experience with Java and Spring, building Kafka Streams applications
- Experience developing ELK-based monitoring solutions
- Strong experience with Logstash Configuration Language (inputs, filters, outputs)
- Experience working with REST APIs
- Experience with SQL (Oracle PL/SQL), including query development and performance tuning
- Familiarity with Kafka CLI and REST APIs for managing Kafka resources
- Experience working in Linux/Unix and Windows environments
- Experience using IntelliJ IDEA
- English level — sufficient for technical communication
Ce serait un plus :
- Experience managing and maintaining ELK servers
- Experience with Confluent Kafka Cloud
- Experience building DevOps processes for Kafka and ELK
- Understanding of best practices in event-driven architecture
Conditions de travail
Semaine de travail de 5 jours, journée de travail de 8 heures ;